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Poster
Mon 1:00 Semantic Re-tuning with Contrastive Tension
Fredrik Carlsson, Amaru C Gyllensten, Evangelia Gogoulou, Erik Y Hellqvist, Magnus Sahlgren
Poster
Mon 1:00 Towards Robust Neural Networks via Close-loop Control
Zhuotong Chen, Qianxiao Li, Zheng Zhang
Poster
Mon 1:00 Stabilized Medical Image Attacks
Gege Qi, Lijun GONG, Yibing Song, Kai Ma, Yefeng Zheng
Poster
Mon 1:00 Neural Approximate Sufficient Statistics for Implicit Models
Yanzhi Chen, Dinghuai Zhang, Michael U Gutmann, Aaron Courville, Zhanxing Zhu
Poster
Mon 1:00 Domain Generalization with MixStyle
Kaiyang Zhou, Yongxin Yang, Yu Qiao, Tao Xiang
Poster
Mon 1:00 Parameter-Based Value Functions
Francesco Faccio, Louis Kirsch, Jürgen Schmidhuber
Poster
Mon 1:00 Is Label Smoothing Truly Incompatible with Knowledge Distillation: An Empirical Study
Zhiqiang Shen, Zhiqiang Shen, Dejia Xu, Zitian Chen, Kwang-Ting Cheng, Marios Savvides
Poster
Mon 1:00 Interpreting and Boosting Dropout from a Game-Theoretic View
Hao Zhang, Sen Li, YinChao Ma, Mingjie Li, Yichen Xie, Quanshi Zhang
Poster
Mon 1:00 Spatially Structured Recurrent Modules
Nasim Rahaman, Anirudh Goyal, Waleed Gondal, Manuel Wuthrich, Stefan Bauer, Yash Sharma, Yoshua Bengio, Bernhard Schoelkopf
Poster
Mon 1:00 Does enhanced shape bias improve neural network robustness to common corruptions?
Chaithanya Kumar Mummadi, Ranjitha Subramaniam, Robin Hutmacher, Julien Vitay, Volker Fischer, Jan Hendrik Metzen
Poster
Mon 1:00 On the Universality of the Double Descent Peak in Ridgeless Regression
David Holzmüller
Poster
Mon 1:00 Uncertainty Estimation and Calibration with Finite-State Probabilistic RNNs
Cheng Wang, Carolin Lawrence, Mathias Niepert
Poster
Mon 1:00 ResNet After All: Neural ODEs and Their Numerical Solution
Katharina Ott, Prateek Katiyar, Philipp Hennig, Michael Tiemann
Poster
Mon 1:00 Targeted Attack against Deep Neural Networks via Flipping Limited Weight Bits
Jiawang Bai, Baoyuan Wu, Yong Zhang, Yiming Li, Zhifeng Li, Shu-Tao Xia
Poster
Mon 1:00 Neural Jump Ordinary Differential Equations: Consistent Continuous-Time Prediction and Filtering
Calypso Herrera, Florian Krach, Josef Teichmann
Poster
Mon 1:00 Wasserstein-2 Generative Networks
Alexander Korotin, Vage Egiazarian, Arip Asadulaev, Alexander Safin, Evgeny Burnaev
Poster
Mon 1:00 MetaNorm: Learning to Normalize Few-Shot Batches Across Domains
Yingjun Du, Xiantong Zhen, Ling Shao, Cees G Snoek
Poster
Mon 1:00 Learning N:M Fine-grained Structured Sparse Neural Networks From Scratch
Aojun Zhou, Yukun Ma, Junnan Zhu, Jianbo Liu, Zhijie Zhang, Kun Yuan, Wenxiu Sun, Hongsheng Li
Poster
Mon 1:00 Rethinking the Role of Gradient-based Attribution Methods for Model Interpretability
Suraj Srinivas, François Fleuret
Oral
Mon 3:00 Dataset Condensation with Gradient Matching
Bo ZHAO, Konda Reddy Mopuri, Hakan Bilen
Spotlight
Mon 3:40 Generalization in data-driven models of primary visual cortex
Konstantin-Klemens Lurz, Mohammad Bashiri, Konstantin Willeke, Akshay Jagadish, Eric Wang, Edgar Walker, Santiago Cadena Cadena, Taliah Muhammad, Erick M Cobos, Andreas Tolias, Alexander S Ecker, Fabian Sinz
Spotlight
Mon 4:30 The Intrinsic Dimension of Images and Its Impact on Learning
Phil Pope, Chen Zhu, Ahmed Abdelkader, Micah Goldblum, Tom Goldstein
Spotlight
Mon 4:40 How Benign is Benign Overfitting ?
Amartya Sanyal, Puneet Dokania, Varun Kanade, Philip Torr
Oral
Mon 5:30 Rethinking the Role of Gradient-based Attribution Methods for Model Interpretability
Suraj Srinivas, François Fleuret
Poster
Mon 9:00 LiftPool: Bidirectional ConvNet Pooling
Jiaojiao Zhao, Cees G Snoek
Poster
Mon 9:00 NeMo: Neural Mesh Models of Contrastive Features for Robust 3D Pose Estimation
Angtian Wang, Adam Kortylewski, Alan Yuille
Poster
Mon 9:00 WrapNet: Neural Net Inference with Ultra-Low-Precision Arithmetic
Renkun Ni, Hong-Min Chu, Oscar Castaneda, Ping-yeh Chiang, Christoph Studer, Tom Goldstein
Poster
Mon 9:00 LambdaNetworks: Modeling long-range Interactions without Attention
Irwan Bello
Poster
Mon 9:00 On Statistical Bias In Active Learning: How and When to Fix It
Sebastian Farquhar, Yarin Gal, Tom Rainforth
Poster
Mon 9:00 Symmetry-Aware Actor-Critic for 3D Molecular Design
Gregor Simm, Robert Pinsler, Gábor Csányi, José Miguel Hernández Lobato
Poster
Mon 9:00 A statistical theory of cold posteriors in deep neural networks
Laurence Aitchison
Poster
Mon 9:00 Gradient Projection Memory for Continual Learning
Gobinda Saha, Isha Garg, Kaushik Roy
Poster
Mon 9:00 Universal approximation power of deep residual neural networks via nonlinear control theory
Paulo Tabuada, Bahman Gharesifard
Poster
Mon 9:00 Shape-Texture Debiased Neural Network Training
Yinigwei Li, Qihang Yu, Mingxing Tan, Jieru Mei, Peng Tang, Wei Shen, Alan Yuille, Cihang Xie
Poster
Mon 9:00 PAC Confidence Predictions for Deep Neural Network Classifiers
Sangdon Park, Shuo Li, Insup Lee, Osbert Bastani
Poster
Mon 9:00 Vector-output ReLU Neural Network Problems are Copositive Programs: Convex Analysis of Two Layer Networks and Polynomial-time Algorithms
Arda Sahiner, Tolga Ergen, John M Pauly, Mert Pilanci
Poster
Mon 9:00 Teaching Temporal Logics to Neural Networks
Christopher Hahn, Frederik Schmitt, Jens Kreber, Markus Rabe, Bernd Finkbeiner
Poster
Mon 9:00 Overparameterisation and worst-case generalisation: friend or foe?
Aditya Krishna Menon, Ankit Singh Rawat, Sanjiv Kumar
Poster
Mon 9:00 Pruning Neural Networks at Initialization: Why Are We Missing the Mark?
Jonathan Frankle, Gintare Dziugaite, Anonymous A Author, Michael Carbin
Poster
Mon 9:00 Selectivity considered harmful: evaluating the causal impact of class selectivity in DNNs
Matthew Leavitt, Ari Morcos
Poster
Mon 9:00 Understanding the failure modes of out-of-distribution generalization
Vaishnavh Nagarajan, Anders J Andreassen, Behnam Neyshabur
Oral
Mon 11:00 Federated Learning Based on Dynamic Regularization
Durmus Alp Emre Acar, Yue Zhao, Ramon Matas, Matthew Mattina, Paul Whatmough, Venkatesh Saligrama
Oral
Mon 11:15 Gradient Projection Memory for Continual Learning
Gobinda Saha, Isha Garg, Kaushik Roy
Spotlight
Mon 12:45 On Statistical Bias In Active Learning: How and When to Fix It
Sebastian Farquhar, Yarin Gal, Tom Rainforth
Poster
Mon 17:00 Robust Curriculum Learning: from clean label detection to noisy label self-correction
Tianyi Zhou, Shengjie Wang, Jeff Bilmes
Poster
Mon 17:00 Online Adversarial Purification based on Self-supervised Learning
Changhao Shi, Chester Holtz, Gal Mishne
Poster
Mon 17:00 SAFENet: A Secure, Accurate and Fast Neural Network Inference
Qian Lou, Yilin Shen, Hongxia Jin, Lei Jiang
Poster
Mon 17:00 One Network Fits All? Modular versus Monolithic Task Formulations in Neural Networks
Atish Agarwala, Abhimanyu Das, Brendan Juba, Rina Panigrahy, Vatsal Sharan, Xin Wang, Qiuyi Zhang
Poster
Mon 17:00 On Dyadic Fairness: Exploring and Mitigating Bias in Graph Connections
Peizhao Li, Yifei Wang, Han Zhao, Pengyu Hong, Hongfu Liu
Poster
Mon 17:00 Optimizing Memory Placement using Evolutionary Graph Reinforcement Learning
Shauharda Khadka, Estelle Aflalo, Mattias Marder, Avrech Ben-David, Santiago Miret, Shie Mannor, Tamir Hazan, Hanlin Tang, Somdeb Majumdar
Poster
Mon 17:00 The Intrinsic Dimension of Images and Its Impact on Learning
Phil Pope, Chen Zhu, Ahmed Abdelkader, Micah Goldblum, Tom Goldstein
Poster
Mon 17:00 Federated Learning Based on Dynamic Regularization
Durmus Alp Emre Acar, Yue Zhao, Ramon Matas, Matthew Mattina, Paul Whatmough, Venkatesh Saligrama
Poster
Mon 17:00 Score-Based Generative Modeling through Stochastic Differential Equations
Yang Song, Jascha Sohl-Dickstein, Durk Kingma, Abhishek Kumar, Stefano Ermon, Ben Poole
Poster
Mon 17:00 Neural Attention Distillation: Erasing Backdoor Triggers from Deep Neural Networks
Yige Li, Xixiang Lyu, Nodens Koren, Lingjuan Lyu, Bo Li, Daniel Ma
Poster
Mon 17:00 Incorporating Symmetry into Deep Dynamics Models for Improved Generalization
Rui Wang, Robin Walters, Rose Yu
Poster
Mon 17:00 Optimal Regularization can Mitigate Double Descent
Preetum Nakkiran, Prayaag Venkat, Sham M Kakade, Tengyu Ma
Poster
Mon 17:00 On the geometry of generalization and memorization in deep neural networks
Cory Stephenson, Suchi Padhy, Abhinav Ganesh, Yue Hui, Hanlin Tang, SueYeon Chung
Poster
Mon 17:00 Robust and Generalizable Visual Representation Learning via Random Convolutions
Zhenlin Xu, Deyi Liu, Junlin Yang, Colin Raffel, Marc Niethammer
Poster
Mon 17:00 Regularization Matters in Policy Optimization - An Empirical Study on Continuous Control
Zhuang Liu, Xuanlin Li, Bingyi Kang, trevor darrell
Poster
Mon 17:00 Spatio-Temporal Graph Scattering Transform
Chao Pan, Siheng Chen, Antonio Ortega
Poster
Mon 17:00 Zero-shot Synthesis with Group-Supervised Learning
Yunhao Ge, Sami Abu-El-Haija, Gan Xin, Laurent Itti
Spotlight
Mon 20:18 Improving Adversarial Robustness via Channel-wise Activation Suppressing
Yang Bai, Yuyuan Zeng, Yong Jiang, Shu-Tao Xia, Daniel Ma, Yisen Wang
Spotlight
Mon 20:28 Fast Geometric Projections for Local Robustness Certification
Aymeric Fromherz, Klas Leino, Matt Fredrikson, Bryan Parno, Corina Pasareanu
Spotlight
Mon 20:58 HW-NAS-Bench: Hardware-Aware Neural Architecture Search Benchmark
Chaojian Li, Zhongzhi Yu, Yonggan Fu, Yongan Zhang, Yang Zhao, Haoran You, Qixuan Yu, Yue Wang, Cong Hao, Yingyan Lin
Oral
Mon 21:21 How Neural Networks Extrapolate: From Feedforward to Graph Neural Networks
Keyulu Xu, Mozhi Zhang, Jingling Li, Simon Du, Ken-Ichi Kawarabayashi, Stefanie Jegelka
Invited Talk
Tue 0:00 Geometric Deep Learning: the Erlangen Programme of ML
Michael Bronstein
Poster
Tue 1:00 A Block Minifloat Representation for Training Deep Neural Networks
Sean Fox, Seyedramin Rasoulinezhad, Julian Faraone, david boland, Philip Leong
Poster
Tue 1:00 AdaGCN: Adaboosting Graph Convolutional Networks into Deep Models
Ke Sun, Zhanxing Zhu, Zhouchen Lin
Poster
Tue 1:00 Conformation-Guided Molecular Representation with Hamiltonian Neural Networks
Ziyao Li, Shuwen Yang, Guojie Song, Lingsheng Cai
Poster
Tue 1:00 Intraclass clustering: an implicit learning ability that regularizes DNNs
Simon Carbonnelle, Christophe De Vleeschouwer
Poster
Tue 1:00 Computational Separation Between Convolutional and Fully-Connected Networks
Eran Malach, Shai Shalev-Shwartz
Poster
Tue 1:00 Auxiliary Learning by Implicit Differentiation
Aviv Navon, Idan Achituve, Haggai Maron, Gal Chechik, Ethan Fetaya
Poster
Tue 1:00 Practical Real Time Recurrent Learning with a Sparse Approximation
Jacob Menick, Erich Elsen, Utku Evci, Simon Osindero, Karen Simonyan, Alex Graves
Poster
Tue 1:00 Learning Incompressible Fluid Dynamics from Scratch - Towards Fast, Differentiable Fluid Models that Generalize
Nils Wandel, Michael Weinmann, Reinhard Klein
Poster
Tue 1:00 Large-width functional asymptotics for deep Gaussian neural networks
Daniele Bracale, Stefano Favaro, Sandra Fortini, Stefano Peluchetti
Poster
Tue 1:00 Learning Accurate Entropy Model with Global Reference for Image Compression
Yichen Qian, Zhiyu Tan, Xiuyu Sun, Ming Lin, Dongyang Li, Zhenhong Sun, Li Hao, Rong Jin
Poster
Tue 1:00 Effective Abstract Reasoning with Dual-Contrast Network
Tao Zhuo, Mohan Kankanhalli
Poster
Tue 1:00 Image GANs meet Differentiable Rendering for Inverse Graphics and Interpretable 3D Neural Rendering
Yuxuan Zhang, Wenzheng Chen, Huan Ling, Jun Gao, Yinan Zhang, Antonio Torralba, Sanja Fidler
Poster
Tue 1:00 Hyperbolic Neural Networks++
Ryohei Shimizu, YUSUKE Mukuta, Tatsuya Harada
Poster
Tue 1:00 Activation-level uncertainty in deep neural networks
Pablo Morales-Alvarez, Daniel Hernández-Lobato, Rafael Molina, José Miguel Hernández Lobato
Poster
Tue 1:00 SkipW: Resource Adaptable RNN with Strict Upper Computational Limit
Tsiry MAYET, Anne Lambert, Pascal Le Guyadec, Francoise Le Bolzer, François Schnitzler
Poster
Tue 1:00 Learning Better Structured Representations Using Low-rank Adaptive Label Smoothing
Asish Ghoshal, Xilun Chen, Sonal Gupta, Luke Zettlemoyer, Yashar Mehdad
Poster
Tue 1:00 A Trainable Optimal Transport Embedding for Feature Aggregation and its Relationship to Attention
Grégoire Mialon, Dexiong Chen, Alexandre d'Aspremont, Julien Mairal
Poster
Tue 1:00 Spatial Dependency Networks: Neural Layers for Improved Generative Image Modeling
Đorđe Miladinović, Aleksandar Stanić, Stefan Bauer, Jürgen Schmidhuber, Joachim M Buhmann
Poster
Tue 1:00 Generalization in data-driven models of primary visual cortex
Konstantin-Klemens Lurz, Mohammad Bashiri, Konstantin Willeke, Akshay Jagadish, Eric Wang, Edgar Walker, Santiago Cadena Cadena, Taliah Muhammad, Erick M Cobos, Andreas Tolias, Alexander S Ecker, Fabian Sinz
Poster
Tue 1:00 Identifying nonlinear dynamical systems with multiple time scales and long-range dependencies
Dominik Schmidt, Georgia Koppe, Zahra Monfared, Max Beutelspacher, Daniel Durstewitz
Poster
Tue 1:00 Lossless Compression of Structured Convolutional Models via Lifting
Gustav Sourek, Filip Zelezny, Ondrej Kuzelka
Poster
Tue 1:00 Exemplary Natural Images Explain CNN Activations Better than State-of-the-Art Feature Visualization
Judy Borowski, Roland Zimmermann, Judith Schepers, Robert Geirhos, Thomas S Wallis, Matthias Bethge, Wieland Brendel
Poster
Tue 1:00 Accurate Learning of Graph Representations with Graph Multiset Pooling
Jinheon Baek, Minki Kang, Sung Ju Hwang
Spotlight
Tue 3:25 Interpreting Graph Neural Networks for NLP With Differentiable Edge Masking
Michael Schlichtkrull, Nicola De Cao, Ivan Titov
Spotlight
Tue 3:35 Expressive Power of Invariant and Equivariant Graph Neural Networks
Waïss Azizian, marc lelarge
Spotlight
Tue 5:18 Learning Incompressible Fluid Dynamics from Scratch - Towards Fast, Differentiable Fluid Models that Generalize
Nils Wandel, Michael Weinmann, Reinhard Klein
Spotlight
Tue 5:28 Identifying nonlinear dynamical systems with multiple time scales and long-range dependencies
Dominik Schmidt, Georgia Koppe, Zahra Monfared, Max Beutelspacher, Daniel Durstewitz
Poster
Tue 9:00 Getting a CLUE: A Method for Explaining Uncertainty Estimates
Javier Antorán, Umang Bhatt, Tameem Adel, Adrian Weller, José Miguel Hernández Lobato
Poster
Tue 9:00 NOVAS: Non-convex Optimization via Adaptive Stochastic Search for End-to-end Learning and Control
Ioannis Exarchos, Marcus A Pereira, Ziyi Wang, Evangelos Theodorou
Poster
Tue 9:00 Mapping the Timescale Organization of Neural Language Models
Hsiang-Yun Sherry Chien, Jinhan Zhang, Christopher Honey
Poster
Tue 9:00 Learning Parametrised Graph Shift Operators
George Dasoulas, Johannes Lutzeyer, Michalis Vazirgiannis
Poster
Tue 9:00 Are wider nets better given the same number of parameters?
Anna Golubeva, Guy Gur-Ari, Behnam Neyshabur
Poster
Tue 9:00 Training BatchNorm and Only BatchNorm: On the Expressive Power of Random Features in CNNs
Jonathan Frankle, David J Schwab, Ari Morcos
Poster
Tue 9:00 Transient Non-stationarity and Generalisation in Deep Reinforcement Learning
Maximilian Igl, Gregory Farquhar, Jelena Luketina, Wendelin Boehmer, Shimon Whiteson
Poster
Tue 9:00 The geometry of integration in text classification RNNs
Kyle Aitken, Vinay Ramasesh, Ankush Garg, Yuan Cao, David Sussillo, Niru Maheswaranathan
Poster
Tue 9:00 Teaching with Commentaries
Aniruddh Raghu, Maithra Raghu, Simon Kornblith, David Duvenaud, Geoffrey Hinton
Poster
Tue 9:00 Learning from Protein Structure with Geometric Vector Perceptrons
Bowen Jing, Stephan Eismann, Patricia Suriana, Raphael J Townshend, Ron Dror
Poster
Tue 9:00 Reducing the Computational Cost of Deep Generative Models with Binary Neural Networks
Thomas Bird, Friso Kingma, David Barber
Poster
Tue 9:00 Robust Pruning at Initialization
Soufiane Hayou, Jean-Francois Ton, Arnaud Doucet, Yee Whye Teh
Poster
Tue 9:00 Distance-Based Regularisation of Deep Networks for Fine-Tuning
Henry Gouk, Timothy Hospedales, massimiliano pontil
Poster
Tue 9:00 Characterizing signal propagation to close the performance gap in unnormalized ResNets
Andrew Brock, Soham De, Samuel Smith
Poster
Tue 9:00 How Benign is Benign Overfitting ?
Amartya Sanyal, Puneet Dokania, Varun Kanade, Philip Torr
Poster
Tue 9:00 DialoGraph: Incorporating Interpretable Strategy-Graph Networks into Negotiation Dialogues
Rishabh Joshi, Vidhisha Balachandran, Shikhar Vashishth, Alan Black, Yulia Tsvetkov
Poster
Tue 9:00 Global optimality of softmax policy gradient with single hidden layer neural networks in the mean-field regime
Andrea Agazzi, Jianfeng Lu
Poster
Tue 9:00 On the Dynamics of Training Attention Models
Haoye Lu, Yongyi Mao, Amiya Nayak
Poster
Tue 9:00 SSD: A Unified Framework for Self-Supervised Outlier Detection
Vikash Sehwag, Mung Chiang, Prateek Mittal
Poster
Tue 9:00 Single-Timescale Actor-Critic Provably Finds Globally Optimal Policy
Zuyue Fu, Zhuoran Yang, Zhaoran Wang
Oral
Tue 12:15 Image GANs meet Differentiable Rendering for Inverse Graphics and Interpretable 3D Neural Rendering
Yuxuan Zhang, Wenzheng Chen, Huan Ling, Jun Gao, Yinan Zhang, Antonio Torralba, Sanja Fidler
Spotlight
Tue 12:40 Implicit Convex Regularizers of CNN Architectures: Convex Optimization of Two- and Three-Layer Networks in Polynomial Time
Tolga Ergen, Mert Pilanci
Spotlight
Tue 12:50 Learning from Protein Structure with Geometric Vector Perceptrons
Bowen Jing, Stephan Eismann, Patricia Suriana, Raphael J Townshend, Ron Dror
Poster
Tue 17:00 A Temporal Kernel Approach for Deep Learning with Continuous-time Information
Da Xu, Chuanwei Ruan, evren korpeoglu, Sushant Kumar, kannan achan
Poster
Tue 17:00 Fantastic Four: Differentiable and Efficient Bounds on Singular Values of Convolution Layers
ssingla Singla, Soheil Feizi
Poster
Tue 17:00 CopulaGNN: Towards Integrating Representational and Correlational Roles of Graphs in Graph Neural Networks
Jiaqi Ma, Bo Chang, Xuefei Zhang, Qiaozhu Mei
Poster
Tue 17:00 Gradient Descent on Neural Networks Typically Occurs at the Edge of Stability
Jeremy Cohen, Simran Kaur, Yuanzhi Li, Zico Kolter, Ameet Talwalkar
Poster
Tue 17:00 Attentional Constellation Nets for Few-Shot Learning
Weijian Xu, Yifan Xu, Huaijin Wang, Zhuowen Tu
Poster
Tue 17:00 How to Find Your Friendly Neighborhood: Graph Attention Design with Self-Supervision
Dongkwan Kim, Alice Oh
Poster
Tue 17:00 Contextual Dropout: An Efficient Sample-Dependent Dropout Module
XINJIE FAN, Shujian Zhang, Korawat Tanwisuth, Xiaoning Qian, Mingyuan Zhou
Poster
Tue 17:00 DDPNOpt: Differential Dynamic Programming Neural Optimizer
Guan-Horng Liu, Tianrong Chen, Evangelos Theodorou
Poster
Tue 17:00 Co-Mixup: Saliency Guided Joint Mixup with Supermodular Diversity
Jang-Hyun Kim, Wonho Choo, Hosan Jeong, Hyun Oh Song
Poster
Tue 17:00 Discrete Graph Structure Learning for Forecasting Multiple Time Series
Chao Shang, Jie Chen, Jinbo Bi
Poster
Tue 17:00 Do Wide and Deep Networks Learn the Same Things? Uncovering How Neural Network Representations Vary with Width and Depth
Thao Nguyen, Maithra Raghu, Simon Kornblith
Poster
Tue 17:00 A unifying view on implicit bias in training linear neural networks
Chulhee (Charlie) Yun, Shankar Krishnan, Hossein Mobahi
Poster
Tue 17:00 Linear Mode Connectivity in Multitask and Continual Learning
Seyed Iman Mirzadeh, Mehrdad Farajtabar, Dilan Gorur, Razvan Pascanu, Hassan Ghasemzadeh
Poster
Tue 17:00 FedBE: Making Bayesian Model Ensemble Applicable to Federated Learning
Hong-You Chen, Wei-Lun Chao
Poster
Tue 17:00 Fuzzy Tiling Activations: A Simple Approach to Learning Sparse Representations Online
Yangchen Pan, Kirby Banman, Martha White
Poster
Tue 17:00 SEDONA: Search for Decoupled Neural Networks toward Greedy Block-wise Learning
Myeongjang Pyeon, Jihwan Moon, Taeyoung Hahn, Gunhee Kim
Poster
Tue 17:00 Implicit Convex Regularizers of CNN Architectures: Convex Optimization of Two- and Three-Layer Networks in Polynomial Time
Tolga Ergen, Mert Pilanci
Poster
Tue 17:00 A Discriminative Gaussian Mixture Model with Sparsity
Hideaki Hayashi, Seiichi Uchida
Poster
Tue 17:00 On Graph Neural Networks versus Graph-Augmented MLPs
Lei Chen, Zhengdao Chen, Joan Bruna
Poster
Tue 17:00 Lipschitz Recurrent Neural Networks
N. Benjamin Erichson, Omri Azencot, Alejandro Queiruga, Liam Hodgkinson, Michael W Mahoney
Poster
Tue 17:00 Generalized Variational Continual Learning
Noel Loo, Siddharth Swaroop, Rich E Turner
Poster
Tue 17:00 Convex Potential Flows: Universal Probability Distributions with Optimal Transport and Convex Optimization
Chin-Wei Huang, Ricky T. Q. Chen, Christos Tsirigotis, Aaron Courville
Poster
Tue 17:00 How Neural Networks Extrapolate: From Feedforward to Graph Neural Networks
Keyulu Xu, Mozhi Zhang, Jingling Li, Simon Du, Ken-Ichi Kawarabayashi, Stefanie Jegelka
Poster
Tue 17:00 Fourier Neural Operator for Parametric Partial Differential Equations
Zongyi Li, Nikola B Kovachki, Kamyar Azizzadenesheli, Burigede liu, Kaushik Bhattacharya, Andrew Stuart, Anima Anandkumar
Poster
Tue 17:00 Why Are Convolutional Nets More Sample-Efficient than Fully-Connected Nets?
Zhiyuan Li, Yi Zhang, Sanjeev Arora
Poster
Tue 17:00 Implicit Under-Parameterization Inhibits Data-Efficient Deep Reinforcement Learning
Aviral Kumar, Rishabh Agarwal, Dibya Ghosh, Sergey Levine
Oral
Tue 19:00 Deep symbolic regression: Recovering mathematical expressions from data via risk-seeking policy gradients
Brenden Petersen, Mikel Landajuela Larma, Terrell N Mundhenk, Claudio Santiago, Soo Kim, Joanne Kim
Spotlight
Tue 19:15 DDPNOpt: Differential Dynamic Programming Neural Optimizer
Guan-Horng Liu, Tianrong Chen, Evangelos Theodorou
Oral
Tue 19:55 Global Convergence of Three-layer Neural Networks in the Mean Field Regime
Huy Tuan Pham, Phan-Minh Nguyen
Spotlight
Tue 20:10 Minimum Width for Universal Approximation
Sejun Park, Chulhee (Charlie) Yun, Jaeho Lee, Jinwoo Shin
Oral
Tue 21:03 Co-Mixup: Saliency Guided Joint Mixup with Supermodular Diversity
Jang-Hyun Kim, Wonho Choo, Hosan Jeong, Hyun Oh Song
Spotlight
Tue 21:33 Locally Free Weight Sharing for Network Width Search
Xiu Su, Shan You, Tao Huang, Fei Wang, Chen Qian, Changshui Zhang, Chang Xu
Poster
Wed 1:00 Improving Adversarial Robustness via Channel-wise Activation Suppressing
Yang Bai, Yuyuan Zeng, Yong Jiang, Shu-Tao Xia, Daniel Ma, Yisen Wang
Poster
Wed 1:00 IEPT: Instance-Level and Episode-Level Pretext Tasks for Few-Shot Learning
Manli Zhang, Jianhong Zhang, Zhiwu Lu, Tao Xiang, Mingyu Ding, Songfang Huang
Poster
Wed 1:00 BRECQ: Pushing the Limit of Post-Training Quantization by Block Reconstruction
Yuhang Li, Ruihao Gong, Xu Tan, Yang Yang, Peng Hu, Qi Zhang, fengwei yu, Wei Wang, Shi Gu
Poster
Wed 1:00 Removing Undesirable Feature Contributions Using Out-of-Distribution Data
Saehyung Lee, Changhwa Park, Hyungyu Lee, Jihun Yi, Jonghyun Lee, Sungroh Yoon
Poster
Wed 1:00 Neural networks with late-phase weights
Johannes von Oswald, Seijin Kobayashi, Joao Sacramento, Alexander Meulemans, Christian Henning, Benjamin F Grewe
Poster
Wed 1:00 A Panda? No, It's a Sloth: Slowdown Attacks on Adaptive Multi-Exit Neural Network Inference
Sanghyun Hong, Yigitcan Kaya, Ionut-Vlad Modoranu, Tudor Dumitras
Poster
Wed 1:00 Degree-Quant: Quantization-Aware Training for Graph Neural Networks
Shyam Tailor, Javier Fernandez-Marques, Nic Lane
Poster
Wed 1:00 Locally Free Weight Sharing for Network Width Search
Xiu Su, Shan You, Tao Huang, Fei Wang, Chen Qian, Changshui Zhang, Chang Xu
Poster
Wed 1:00 Fooling a Complete Neural Network Verifier
Dániel Zombori, Balázs Bánhelyi, Tibor Csendes, István Megyeri, Márk Jelasity
Poster
Wed 1:00 Expressive Power of Invariant and Equivariant Graph Neural Networks
Waïss Azizian, marc lelarge
Poster
Wed 1:00 Learning Associative Inference Using Fast Weight Memory
Imanol Schlag, Tsendsuren Munkhdalai, Jürgen Schmidhuber
Poster
Wed 1:00 Net-DNF: Effective Deep Modeling of Tabular Data
Liran Katzir, Gal Elidan, Ran El-Yaniv
Poster
Wed 1:00 Neural Delay Differential Equations
Qunxi Zhu, Yao Guo, Wei Lin
Poster
Wed 1:00 Graph Edit Networks
Benjamin Paassen, Daniele Grattarola, Daniele Zambon, Cesare Alippi, Barbara E Hammer
Poster
Wed 1:00 Reweighting Augmented Samples by Minimizing the Maximal Expected Loss
Mingyang Yi, LU HOU, Lifeng Shang, Xin Jiang, Qun Liu, Zhi-Ming Ma
Poster
Wed 1:00 Grounded Language Learning Fast and Slow
Felix Hill, Olivier Tieleman, Tamara von Glehn, Nathaniel Wong, Hamza Merzic, Stephen Clark
Poster
Wed 1:00 Simple Spectral Graph Convolution
Hao Zhu, Piotr Koniusz
Poster
Wed 1:00 Byzantine-Resilient Non-Convex Stochastic Gradient Descent
Zeyuan Allen-Zhu, Faeze Ebrahimianghazani, Jerry Li, Dan Alistarh
Oral
Wed 4:05 Getting a CLUE: A Method for Explaining Uncertainty Estimates
Javier Antorán, Umang Bhatt, Tameem Adel, Adrian Weller, José Miguel Hernández Lobato
Spotlight
Wed 4:30 Stabilized Medical Image Attacks
Gege Qi, Lijun GONG, Yibing Song, Kai Ma, Yefeng Zheng
Spotlight
Wed 5:35 Neural Approximate Sufficient Statistics for Implicit Models
Yanzhi Chen, Dinghuai Zhang, Michael U Gutmann, Aaron Courville, Zhanxing Zhu
Wed 6:00 Panel discussion on model efficiency and quantization
Poster
Wed 9:00 Probabilistic Numeric Convolutional Neural Networks
Marc Finzi, Roberto Bondesan, Max Welling
Poster
Wed 9:00 My Body is a Cage: the Role of Morphology in Graph-Based Incompatible Control
Vitaly Kurin, Maximilian Igl, Tim Rocktaeschel, Wendelin Boehmer, Shimon Whiteson
Poster
Wed 9:00 Training independent subnetworks for robust prediction
Marton Havasi, Rodolphe Jenatton, Stanislav Fort, Jeremiah Zhe Liu, Jasper Snoek, Balaji Lakshminarayanan, Andrew Dai, Dustin Tran
Poster
Wed 9:00 Anchor & Transform: Learning Sparse Embeddings for Large Vocabularies
Paul Pu Liang, Manzil Zaheer, Yuan Wang, Amr Ahmed
Poster
Wed 9:00 Variational State-Space Models for Localisation and Dense 3D Mapping in 6 DoF
Atanas Mirchev, Baris Kayalibay, Patrick van der Smagt, Justin Bayer
Poster
Wed 9:00 Exploring the Uncertainty Properties of Neural Networks’ Implicit Priors in the Infinite-Width Limit
Ben Adlam, Jaehoon Lee, Lechao Xiao, Jeffrey Pennington, Jasper Snoek
Poster
Wed 9:00 Perceptual Adversarial Robustness: Defense Against Unseen Threat Models
Cassidy Laidlaw, ssingla Singla, Soheil Feizi
Poster
Wed 9:00 Interpreting Graph Neural Networks for NLP With Differentiable Edge Masking
Michael Schlichtkrull, Nicola De Cao, Ivan Titov
Poster
Wed 9:00 Learning Mesh-Based Simulation with Graph Networks
Tobias Pfaff, Meire Fortunato, Alvaro Sanchez Gonzalez, Peter Battaglia
Poster
Wed 9:00 Entropic gradient descent algorithms and wide flat minima
Fabrizio Pittorino, Carlo Lucibello, Christoph Feinauer, Gabriele Perugini, Carlo Baldassi, Elizaveta Demyanenko, Riccardo Zecchina
Poster
Wed 9:00 Multiplicative Filter Networks
Rizal Fathony, Anit Kumar Sahu, Devin Willmott, Zico Kolter
Poster
Wed 9:00 Continuous Wasserstein-2 Barycenter Estimation without Minimax Optimization
Alexander Korotin, Lingxiao Li, Justin Solomon, Evgeny Burnaev
Poster
Wed 9:00 Are Neural Nets Modular? Inspecting Functional Modularity Through Differentiable Weight Masks
Robert Csordas, Sjoerd van Steenkiste, Jürgen Schmidhuber
Poster
Wed 9:00 Coupled Oscillatory Recurrent Neural Network (coRNN): An accurate and (gradient) stable architecture for learning long time dependencies
T. Konstantin Rusch, Siddhartha Mishra
Poster
Wed 9:00 Learning advanced mathematical computations from examples
François Charton, Amaury Hayat, Guillaume Lample
Poster
Wed 9:00 Neural Networks for Learning Counterfactual G-Invariances from Single Environments
S Chandra Mouli, Bruno Ribeiro
Poster
Wed 9:00 Deep symbolic regression: Recovering mathematical expressions from data via risk-seeking policy gradients
Brenden Petersen, Mikel Landajuela Larma, Terrell N Mundhenk, Claudio Santiago, Soo Kim, Joanne Kim
Poster
Wed 9:00 On the Bottleneck of Graph Neural Networks and its Practical Implications
Uri Alon, Eran Yahav
Poster
Wed 9:00 Witches' Brew: Industrial Scale Data Poisoning via Gradient Matching
Jonas Geiping, Liam H Fowl, Ronny Huang, Wojciech Czaja, Gavin Taylor, Michael Moeller, Tom Goldstein
Poster
Wed 9:00 TropEx: An Algorithm for Extracting Linear Terms in Deep Neural Networks
Martin Trimmel, Henning Petzka, Cristian Sminchisescu
Poster
Wed 9:00 More or Less: When and How to Build Convolutional Neural Network Ensembles
Abdul Wasay, Stratos Idreos
Poster
Wed 9:00 Graph Information Bottleneck for Subgraph Recognition
Junchi Yu, Tingyang Xu, Yu Rong, Yatao Bian, Junzhou Huang, Ran He
Poster
Wed 9:00 Boost then Convolve: Gradient Boosting Meets Graph Neural Networks
Sergei Ivanov, Liudmila Prokhorenkova
Oral
Wed 12:23 Coupled Oscillatory Recurrent Neural Network (coRNN): An accurate and (gradient) stable architecture for learning long time dependencies
T. Konstantin Rusch, Siddhartha Mishra
Spotlight
Wed 12:48 LambdaNetworks: Modeling long-range Interactions without Attention
Irwan Bello
Spotlight
Wed 12:58 Grounded Language Learning Fast and Slow
Felix Hill, Olivier Tieleman, Tamara von Glehn, Nathaniel Wong, Hamza Merzic, Stephen Clark
Spotlight
Wed 13:58 Differentially Private Learning Needs Better Features (or Much More Data)
Florian Tramer, Dan Boneh
Oral
Wed 16:30 Score-Based Generative Modeling through Stochastic Differential Equations
Yang Song, Jascha Sohl-Dickstein, Durk Kingma, Abhishek Kumar, Stefano Ermon, Ben Poole
Spotlight
Wed 16:45 Learning Mesh-Based Simulation with Graph Networks
Tobias Pfaff, Meire Fortunato, Alvaro Sanchez Gonzalez, Peter Battaglia
Poster
Wed 17:00 Efficient Empowerment Estimation for Unsupervised Stabilization
Ruihan Zhao, Kevin Lu, Pieter Abbeel, Stas Tiomkin
Poster
Wed 17:00 CPR: Classifier-Projection Regularization for Continual Learning
Sungmin Cha, Hsiang Hsu, Taebaek Hwang, Flavio Calmon, Taesup Moon
Poster
Wed 17:00 Protecting DNNs from Theft using an Ensemble of Diverse Models
Sanjay Kariyappa, Atul Prakash, Moinuddin K Qureshi
Poster
Wed 17:00 INT: An Inequality Benchmark for Evaluating Generalization in Theorem Proving
Yuhuai Wu, Albert Jiang, Jimmy Ba, Roger Grosse
Poster
Wed 17:00 Effective and Efficient Vote Attack on Capsule Networks
Jindong Gu, Baoyuan Wu, Volker Tresp
Poster
Wed 17:00 Learning with Instance-Dependent Label Noise: A Sample Sieve Approach
Hao Cheng, Zhaowei Zhu, Xingyu Li, Yifei Gong, Xing Sun, Yang Liu
Poster
Wed 17:00 A PAC-Bayesian Approach to Generalization Bounds for Graph Neural Networks
Renjie Liao, Raquel Urtasun, Richard Zemel
Poster
Wed 17:00 Learning Manifold Patch-Based Representations of Man-Made Shapes
Dmitriy Smirnov, Mikhail Bessmeltsev, Justin Solomon
Poster
Wed 17:00 Economic Hyperparameter Optimization With Blended Search Strategy
Chi Wang, Qingyun Wu, Silu Huang, Amin Saied
Poster
Wed 17:00 Neural Architecture Search on ImageNet in Four GPU Hours: A Theoretically Inspired Perspective
Wuyang Chen, Xinyu Gong, Zhangyang Wang
Poster
Wed 17:00 Combining Physics and Machine Learning for Network Flow Estimation
Arlei Lopes da Silva, Furkan Kocayusufoglu, Saber Jafarpour, Francesco Bullo, Ananthram Swami, Ambuj K Singh
Poster
Wed 17:00 Simple Augmentation Goes a Long Way: ADRL for DNN Quantization
Lin Ning, Guoyang Chen, Weifeng Zhang, Xipeng Shen
Poster
Wed 17:00 NBDT: Neural-Backed Decision Tree
Alvin Wan, Lisa Dunlap, Daniel Ho, Jihan Yin, Scott Lee, Suzanne Petryk, Sarah A Bargal, Joseph E Gonzalez
Poster
Wed 17:00 Adaptive Universal Generalized PageRank Graph Neural Network
Eli Chien, Jianhao Peng, Pan Li, Olgica Milenkovic
Spotlight
Wed 21:25 Regularization Matters in Policy Optimization - An Empirical Study on Continuous Control
Zhuang Liu, Xuanlin Li, Bingyi Kang, trevor darrell
Oral
Thu 0:30 Optimal Rates for Averaged Stochastic Gradient Descent under Neural Tangent Kernel Regime
Atsushi Nitanda, Taiji Suzuki
Poster
Thu 1:00 Distilling Knowledge from Reader to Retriever for Question Answering
Gautier Izacard, Edouard Grave
Poster
Thu 1:00 AdamP: Slowing Down the Slowdown for Momentum Optimizers on Scale-invariant Weights
Byeongho Heo, Sanghyuk Chun, Seong Joon Oh, Dongyoon Han, Sangdoo Yun, Gyuwan Kim, Youngjung Uh, Jung-Woo Ha
Poster
Thu 1:00 ChipNet: Budget-Aware Pruning with Heaviside Continuous Approximations
Rishabh Tiwari, Udbhav Bamba, Arnav Chavan, Deepak Gupta
Poster
Thu 1:00 Learning continuous-time PDEs from sparse data with graph neural networks
Valerii Iakovlev, Markus Heinonen, Harri Lähdesmäki
Poster
Thu 1:00 Go with the flow: Adaptive control for Neural ODEs
Mathieu Chalvidal, Matthew Ricci, Rufin VanRullen, Thomas Serre
Poster
Thu 1:00 Optimal Conversion of Conventional Artificial Neural Networks to Spiking Neural Networks
Shikuang Deng, Shi Gu
Poster
Thu 1:00 Network Pruning That Matters: A Case Study on Retraining Variants
Duong Le, Binh-Son Hua
Poster
Thu 1:00 R-GAP: Recursive Gradient Attack on Privacy
Junyi Zhu, Matthew Blaschko
Poster
Thu 1:00 Collective Robustness Certificates: Exploiting Interdependence in Graph Neural Networks
Jan Schuchardt, Aleksandar Bojchevski, Johannes Klicpera, Stephan Günnemann
Poster
Thu 1:00 Interpretable Models for Granger Causality Using Self-explaining Neural Networks
Ričards Marcinkevičs, Julia E Vogt
Poster
Thu 1:00 An Unsupervised Deep Learning Approach for Real-World Image Denoising
Dihan Zheng, Sia Huat Tan, Xiaowen Zhang, Zuoqiang Shi, Kaisheng Ma, Chenglong Bao
Poster
Thu 1:00 Optimal Rates for Averaged Stochastic Gradient Descent under Neural Tangent Kernel Regime
Atsushi Nitanda, Taiji Suzuki
Poster
Thu 1:00 Retrieval-Augmented Generation for Code Summarization via Hybrid GNN
Shangqing Liu, Yu Chen, Xiaofei Xie, Siow Jing Kai, Yang Liu
Poster
Thu 1:00 Practical Massively Parallel Monte-Carlo Tree Search Applied to Molecular Design
Xiufeng Yang, Tanuj Aasawat, Kazuki Yoshizoe
Poster
Thu 1:00 Counterfactual Generative Networks
Axel Sauer, Andreas Geiger
Poster
Thu 1:00 Continual learning in recurrent neural networks
Benjamin Ehret, Christian Henning, Maria Cervera, Alexander Meulemans, Johannes von Oswald, Benjamin F Grewe
Spotlight
Thu 5:05 Retrieval-Augmented Generation for Code Summarization via Hybrid GNN
Shangqing Liu, Yu Chen, Xiaofei Xie, Siow Jing Kai, Yang Liu
Spotlight
Thu 5:15 Practical Real Time Recurrent Learning with a Sparse Approximation
Jacob Menick, Erich Elsen, Utku Evci, Simon Osindero, Karen Simonyan, Alex Graves
Poster
Thu 9:00 Deep Networks and the Multiple Manifold Problem
Sam Buchanan, Dar Gilboa, John Wright
Poster
Thu 9:00 Neural Spatio-Temporal Point Processes
Ricky T. Q. Chen, Brandon Amos, Maximilian Nickel
Poster
Thu 9:00 Meta-Learning of Structured Task Distributions in Humans and Machines
Sreejan Kumar, Ishita Dasgupta, Jonathan Cohen, Nathaniel Daw, Thomas L Griffiths
Poster
Thu 9:00 BSQ: Exploring Bit-Level Sparsity for Mixed-Precision Neural Network Quantization
Huanrui Yang, Lin Duan, Yiran Chen, Hai Li
Poster
Thu 9:00 Graph Coarsening with Neural Networks
Chen Cai, Dingkang Wang, Yusu Wang
Poster
Thu 9:00 Dataset Meta-Learning from Kernel Ridge-Regression
Timothy Nguyen, Zhourong Chen, Jaehoon Lee
Poster
Thu 9:00 Deconstructing the Regularization of BatchNorm
Yann Dauphin, Ekin Cubuk
Poster
Thu 9:00 Analyzing the Expressive Power of Graph Neural Networks in a Spectral Perspective
Muhammet Balcilar, Guillaume Renton, Pierre Héroux, Benoit Gaüzère, Sébastien Adam, Paul Honeine
Poster
Thu 9:00 Dataset Condensation with Gradient Matching
Bo ZHAO, Konda Reddy Mopuri, Hakan Bilen
Poster
Thu 9:00 Differentially Private Learning Needs Better Features (or Much More Data)
Florian Tramer, Dan Boneh
Poster
Thu 9:00 Learning to live with Dale's principle: ANNs with separate excitatory and inhibitory units
Jonathan Cornford, Damjan Kalajdzievski, Marco Leite, Amélie Lamarquette, Dimitri Kullmann, Blake A Richards
Poster
Thu 9:00 Implicit Gradient Regularization
David Barrett, Benoit Dherin
Poster
Thu 9:00 Adversarially-Trained Deep Nets Transfer Better: Illustration on Image Classification
Francisco Utrera, Evan Kravitz, N. Benjamin Erichson, Rajiv Khanna, Michael W Mahoney
Poster
Thu 9:00 Uncertainty in Gradient Boosting via Ensembles
Andrey Malinin, Liudmila Prokhorenkova, Aleksei Ustimenko
Poster
Thu 9:00 Multi-Class Uncertainty Calibration via Mutual Information Maximization-based Binning
Kanil Patel, William H Beluch, Bin Yang, Michael Pfeiffer, Dan Zhang
Poster
Thu 9:00 Directed Acyclic Graph Neural Networks
Veronika Thost, Jie Chen
Poster
Thu 9:00 Enforcing robust control guarantees within neural network policies
Priya Donti, Melrose Roderick, Mahyar Fazlyab, Zico Kolter
Oral
Thu 11:45 Why Are Convolutional Nets More Sample-Efficient than Fully-Connected Nets?
Zhiyuan Li, Yi Zhang, Sanjeev Arora
Spotlight
Thu 13:30 A Panda? No, It's a Sloth: Slowdown Attacks on Adaptive Multi-Exit Neural Network Inference
Sanghyun Hong, Yigitcan Kaya, Ionut-Vlad Modoranu, Tudor Dumitras
Poster
Thu 17:00 On the Curse of Memory in Recurrent Neural Networks: Approximation and Optimization Analysis
Zhong Li, Jiequn Han, Weinan E, Qianxiao Li
Poster
Thu 17:00 Fast Geometric Projections for Local Robustness Certification
Aymeric Fromherz, Klas Leino, Matt Fredrikson, Bryan Parno, Corina Pasareanu
Poster
Thu 17:00 HW-NAS-Bench: Hardware-Aware Neural Architecture Search Benchmark
Chaojian Li, Zhongzhi Yu, Yonggan Fu, Yongan Zhang, Yang Zhao, Haoran You, Qixuan Yu, Yue Wang, Cong Hao, Yingyan Lin
Poster
Thu 17:00 Representing Partial Programs with Blended Abstract Semantics
Maxwell Nye, Yewen Pu, Matthew Bowers, Jacob Andreas, Joshua B Tenenbaum, Armando Solar-Lezama
Poster
Thu 17:00 Combining Label Propagation and Simple Models out-performs Graph Neural Networks
Qian Huang, Horace He, Abhay Singh, Ser-Nam Lim, Austin Benson
Poster
Thu 17:00 Nonseparable Symplectic Neural Networks
Shiying Xiong, Yunjin Tong, Xingzhe He, Shuqi Yang, Cheng Yang, Bo Zhu
Poster
Thu 17:00 BiPointNet: Binary Neural Network for Point Clouds
Haotong Qin, Zhongang Cai, Mingyuan Zhang, Yifu Ding, Haiyu Zhao, Shuai Yi, Xianglong Liu, Hao Su
Poster
Thu 17:00 Fast and Complete: Enabling Complete Neural Network Verification with Rapid and Massively Parallel Incomplete Verifiers
Kaidi Xu, Huan Zhang, Shiqi Wang, Yihan Wang, Suman Jana, Xue Lin, Cho-Jui Hsieh
Poster
Thu 17:00 ARMOURED: Adversarially Robust MOdels using Unlabeled data by REgularizing Diversity
Kangkang Lu, Alfred Nguyen, Xun Xu, Kiran Chari, Yu Jing Goh, CS Foo
Poster
Thu 17:00 Multi-Prize Lottery Ticket Hypothesis: Finding Accurate Binary Neural Networks by Pruning A Randomly Weighted Network
James Diffenderfer, Bhavya Kailkhura
Poster
Thu 17:00 Calibration of Neural Networks using Splines
Kartik Gupta, Amir Rahimi, Thalaiyasingam Ajanthan, Thomas Mensink, Cristian Sminchisescu, Richard Hartley
Poster
Thu 17:00 Minimum Width for Universal Approximation
Sejun Park, Chulhee (Charlie) Yun, Jaeho Lee, Jinwoo Shin
Poster
Thu 17:00 Clustering-friendly Representation Learning via Instance Discrimination and Feature Decorrelation
Yaling Tao, Kentaro Takagi, Kouta Nakata
Poster
Thu 17:00 Neural Thompson Sampling
Weitong ZHANG, Dongruo Zhou, Lihong Li, Quanquan Gu
Poster
Thu 17:00 Learning Energy-Based Generative Models via Coarse-to-Fine Expanding and Sampling
Yang Zhao, Jianwen Xie, Ping Li
Poster
Thu 17:00 Global Convergence of Three-layer Neural Networks in the Mean Field Regime
Huy Tuan Pham, Phan-Minh Nguyen
Poster
Thu 17:00 Convex Regularization behind Neural Reconstruction
Arda Sahiner, Morteza Mardani, Batu Ozturkler, Mert Pilanci, John M Pauly
Poster
Thu 17:00 How Much Over-parameterization Is Sufficient to Learn Deep ReLU Networks?
Zixiang Chen, Yuan Cao, Difan Zou, Quanquan Gu
Poster
Thu 17:00 The Recurrent Neural Tangent Kernel
Sina Alemohammad, Jack Wang, Randall Balestriero, Richard Baraniuk
Poster
Thu 17:00 Theoretical Analysis of Self-Training with Deep Networks on Unlabeled Data
Colin Wei, Kendrick Shen, Yining Chen, Tengyu Ma
Poster
Thu 17:00 Few-Shot Learning via Learning the Representation, Provably
Simon Du, Wei Hu, Sham M Kakade, Jason Lee, Qi Lei
Poster
Thu 17:00 Neural Pruning via Growing Regularization
Huan Wang, Can Qin, Yulun Zhang, Yun Fu
Oral
Thu 19:00 Theoretical Analysis of Self-Training with Deep Networks on Unlabeled Data
Colin Wei, Kendrick Shen, Yining Chen, Tengyu Ma
Workshop
Fri 6:30 How Can Findings About The Brain Improve AI Systems?
Shinji Nishimoto, Leila Wehbe, Alexander Huth, Javier Turek, Nicole Beckage, Vy Vo, Mariya Toneva, Hsiang-Yun Chien, Shailee Jain, Richard Antonello
Workshop
Fri 6:30 Break & Poster session 1
Workshop
Fri 7:00 Workshop on Weakly Supervised Learning
Benjamin Roth, Barbara Plank, Alex Ratner, Katharina Kann, Dietrich Klakow, Michael Hedderich
Workshop
Fri 7:00 Generalization beyond the training distribution in brains and machines
Christina Funke, Judith Borowski, Drew Linsley, Xavier Boix
Workshop
Fri 7:45 Coffee break and short paper presentations and discussion.
Hernán Lira, Björn Lütjens, Mark Veillette, Dava Newman, Konstantin Klemmer, Sudipan Saha, Matthias Kahl, Lin Xu, Xiaoxiang Zhu, Hiske Overweg, Ioannis N. Athanasiadis, Nayat Sánchez-Pi, Luis Martí
Workshop
Fri 8:29 Detection of COVID-19 Disease using Deep Neural Networks with Ultrasound Imaging
Dennis Hernando Núñez Fernández
Workshop
Fri 9:05 Assessing Physics Informed Neural Networks in Ocean Modelling and Climate Change Applications
Taco de Wolff, Hugo Carrillo Lincopi, Luis Martí, Nayat Sánchez-Pi
Workshop
Fri 9:30 Break & Poster session 2
Workshop
Fri 10:30 Gal Mishne: Visualizing the PHATE of deep neural networks
Gal Mishne
Workshop
Fri 11:40 Deep Kernels with Probabilistic Embeddings for Small-Data Learning
Ankur Mallick
Workshop
Fri 11:40 Spotlight 8: Yunhao Ge, Graph Autoencoder for Graph Compression and Representation Learning
Workshop
Fri 11:51 "Generative Modeling for Music Generation" by Sander Dieleman, DeepMind
Sander Dieleman
Workshop
Fri 14:02 Invited Talk: A deep learning theory for neural networks grounded in physics
Benjamin Scellier
Workshop
Fri 14:50 Don't Stack Layers in Graph Neural Networks, Wire Them Randomly
Diego Valsesia, Giulia Fracastoro, Enrico Magli
Workshop
MPCLeague: Robust 4-party Computation for Privacy-Preserving Machine Learning
Nishat Koti, Arpita Patra, Ajith Suresh
Workshop
Membership Inference Attack on Graph Neural Networks
Iyiola Emmanuel Olatunji, Wolfgang Nejdl, Megha Khosla
Workshop
Practical Defences Against Model Inversion Attacks for Split Neural Networks
Tom Titcombe, Adam Hall, Pavlos Papadopoulos, Daniele Romanini
Workshop
UNDERSTANDING CLIPPED FEDAVG: CONVERGENCE AND CLIENT-LEVEL DIFFERENTIAL PRIVACY
Xinwei Zhang, Xiangyi Chen, Jinfeng Yi, Steven Wu, Mingyi Hong
Workshop
Talk Less, Smile More: Reducing Communication with Distributed Auto-Differentiation
Bradley Baker, Vince Calhoun, Barak Pearlmutter, Sergey Plis
Workshop
PyVertical: A Vertical Federated Learning Framework for Multi-headed SplitNN
Daniele Romanini, Adam Hall, Pavlos Papadopoulos, Tom Titcombe, Abbas Ismail, Tudor Cebere, Robert Sandmann, Robin Roehm, Michael Hoeh
Workshop
FedGraphNN: A Federated Learning System and Benchmark for Graph Neural Networks
Chaoyang He, Keshav Balasubramanian, Emir Ceyani, Yu Rong, Junzhou Huang, Murali Annavaram, Salman Avestimehr
Workshop
Direct Federated Neural Architecture Search
Anubhav Garg, Amit Saha, Debojyoti Dutta
Workshop
A Graphical Model Perspective on Federated Learning
Christos Louizos, Matthias Reisser, Joseph Soriaga, Max Welling
Workshop
SWIFT: Super-fast and Robust Privacy-Preserving Machine Learning
Nishat Koti, Mahak Pancholi, Arpita Patra, Ajith Suresh
Workshop
High-Robustness, Low-Transferability Fingerprinting of Neural Networks
Siyue Wang
Workshop
Non-Singular Adversarial Robustness of Neural Networks
Chia-Yi Hsu, Pin-Yu Chen
Workshop
Baseline Pruning-Based Approach to Trojan Detection in Neural Networks
Peter Bajcsy
Workshop
Subnet Replacement: Deployment-stage backdoor attack against deep neural networks in gray-box setting
Xiangyu QI
Workshop
Sparse Coding Frontend for Robust Neural Networks
Can Bakiskan
Workshop
Self-Constructing Neural Networks through Random Mutation
Samuel Schmidgall
Workshop
Layer-wise Characterization of Latent Information Leakage in Federated Learning
Fan Mo, Anastasia Borovykh, Mohammad Malekzadeh, Hamed Haddadi, Soteris Demetriou
Workshop
COMBO: Conservative Offline Model-Based Policy Optimization
Tianhe (Kevin) Yu, Aviral Kumar, Aravind Rajeswaran, Rafael Rafailov, Sergey Levine, Chelsea Finn