Filter by Keyword:

204 Results

Poster
Mon 1:00 Randomized Ensembled Double Q-Learning: Learning Fast Without a Model
Xinyue Chen, Che Wang, Zijian Zhou, Keith Ross
Poster
Mon 1:00 Isometric Transformation Invariant and Equivariant Graph Convolutional Networks
Masanobu Horie, Naoki Morita, Toshiaki Hishinuma, Yu Ihara, Naoto Mitsume
Poster
Mon 1:00 Batch Reinforcement Learning Through Continuation Method
Yijie Guo, Shengyu Feng, Nicolas Le Roux, Ed H. Chi, Honglak Lee, Minmin Chen
Poster
Mon 1:00 On the Transfer of Disentangled Representations in Realistic Settings
Andrea Dittadi, Frederik Träuble, Francesco Locatello, Manuel Wuthrich, Vaibhav Agrawal, Ole Winther, Stefan Bauer, Bernhard Schoelkopf
Poster
Mon 1:00 Rapid Neural Architecture Search by Learning to Generate Graphs from Datasets
Hayeon Lee, Eunyoung Hyung, Sung Ju Hwang
Poster
Mon 1:00 Uncertainty Estimation and Calibration with Finite-State Probabilistic RNNs
Cheng Wang, Carolin Lawrence, Mathias Niepert
Poster
Mon 1:00 Signatory: differentiable computations of the signature and logsignature transforms, on both CPU and GPU
Patrick Kidger, Terry Lyons
Poster
Mon 1:00 Trusted Multi-View Classification
Zongbo Han, Changqing Zhang, Huazhu FU, Joey T Zhou
Poster
Mon 1:00 MODALS: Modality-agnostic Automated Data Augmentation in the Latent Space
Tsz Him Cheung, Dit-Yan Yeung
Poster
Mon 1:00 Wasserstein Embedding for Graph Learning
Soheil Kolouri, Navid Naderializadeh, Gustavo K Rohde, Heiko Hoffmann
Oral
Mon 3:00 Dataset Condensation with Gradient Matching
Bo ZHAO, Konda Reddy Mopuri, Hakan Bilen
Oral
Mon 5:00 Geometry-aware Instance-reweighted Adversarial Training
Jingfeng Zhang, Jianing ZHU, Gang Niu, Bo Han, Masashi Sugiyama, Mohan Kankanhalli
Mon 6:00 WiML@ICLR 2021 Virtual Panel
Invited Talk
Mon 8:00 Moving beyond the fairness rhetoric in machine learning
Timnit Gebru
Poster
Mon 9:00 Understanding the failure modes of out-of-distribution generalization
Vaishnavh Nagarajan, Anders J Andreassen, Behnam Neyshabur
Poster
Mon 9:00 LambdaNetworks: Modeling long-range Interactions without Attention
Irwan Bello
Poster
Mon 9:00 Multi-Level Local SGD: Distributed SGD for Heterogeneous Hierarchical Networks
Timothy Castiglia, Anirban Das, Stacy Patterson
Poster
Mon 9:00 Fast convergence of stochastic subgradient method under interpolation
Huang Fang, Zhenan Fan, Michael Friedlander
Poster
Mon 9:00 Shapley Explanation Networks
Rui Wang, Xiaoqian Wang, David Inouye
Poster
Mon 9:00 Learning Hyperbolic Representations of Topological Features
Panagiotis Kyriakis, Iordanis Fostiropoulos, Paul Bogdan
Poster
Mon 9:00 Single-Photon Image Classification
Thomas Fischbacher, Luciano Sbaiz
Poster
Mon 9:00 The Traveling Observer Model: Multi-task Learning Through Spatial Variable Embeddings
Elliot Meyerson, Risto Miikkulainen
Poster
Mon 9:00 Language-Agnostic Representation Learning of Source Code from Structure and Context
Daniel Zügner, Tobias Kirschstein, Michele Catasta, Jure Leskovec, Stephan Günnemann
Mon 9:00 Philosophy and AGI (#1)
Poster
Mon 9:00 Adaptive Federated Optimization
Sashank Reddi, Zachary Charles, Manzil Zaheer, Zachary Garrett, Keith Rush, Jakub Konečný, Sanjiv Kumar, Brendan McMahan
Spotlight
Mon 11:45 Geometry-Aware Gradient Algorithms for Neural Architecture Search
Liam Li, Misha Khodak, Nina Balcan, Ameet Talwalkar
Poster
Mon 17:00 Unlearnable Examples: Making Personal Data Unexploitable
Hanxun Huang, Daniel Ma, Sarah Erfani, James Bailey, Yisen Wang
Poster
Mon 17:00 SenSeI: Sensitive Set Invariance for Enforcing Individual Fairness
Mikhail Yurochkin, Yuekai Sun
Poster
Mon 17:00 Parrot: Data-Driven Behavioral Priors for Reinforcement Learning
Avi Singh, Huihan Liu, Gaoyue Zhou, Albert Yu, Nicholas Rhinehart, Sergey Levine
Poster
Mon 17:00 Deep Partition Aggregation: Provable Defenses against General Poisoning Attacks
Alexander Levine, Soheil Feizi
Poster
Mon 17:00 Model Patching: Closing the Subgroup Performance Gap with Data Augmentation
Karan Goel, Albert Gu, Yixuan Li, Christopher Re
Poster
Mon 17:00 PseudoSeg: Designing Pseudo Labels for Semantic Segmentation
Yuliang Zou, Zizhao Zhang, Han Zhang, Chun-Liang Li, Xiao Bian, Jia-Bin Huang, Tomas Pfister
Poster
Mon 17:00 Explaining the Efficacy of Counterfactually Augmented Data
Divyansh Kaushik, Amrith Setlur, Eduard H Hovy, Zachary Lipton
Poster
Mon 17:00 Undistillable: Making A Nasty Teacher That CANNOT teach students
Haoyu Ma, Tianlong Chen, Ting-Kuei Hu, Chenyu You, Xiaohui Xie, Zhangyang Wang
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 Why resampling outperforms reweighting for correcting sampling bias with stochastic gradients
Jing An, Lexing Ying, Yuhua Zhu
Poster
Mon 17:00 MONGOOSE: A Learnable LSH Framework for Efficient Neural Network Training
Beidi Chen, Zichang Liu, Binghui Peng, Zhaozhuo Xu, Jonathan L Li, Tri Dao, Zhao Song, Anshumali Shrivastava, Christopher Re
Oral
Mon 19:30 Parrot: Data-Driven Behavioral Priors for Reinforcement Learning
Avi Singh, Huihan Liu, Gaoyue Zhou, Albert Yu, Nicholas Rhinehart, Sergey Levine
Spotlight
Mon 20:38 Information Laundering for Model Privacy
Xinran Wang, Yu Xiang, Jun Gao, Jie Ding
Spotlight
Mon 20:48 Dataset Inference: Ownership Resolution in Machine Learning
Pratyush Maini, Mohammad Yaghini, Nicolas Papernot
Spotlight
Mon 21:46 The Traveling Observer Model: Multi-task Learning Through Spatial Variable Embeddings
Elliot Meyerson, Risto Miikkulainen
Poster
Tue 1:00 Conformation-Guided Molecular Representation with Hamiltonian Neural Networks
Ziyao Li, Shuwen Yang, Guojie Song, Lingsheng Cai
Poster
Tue 1:00 Calibration tests beyond classification
David Widmann, Fredrik Lindsten, Dave Zachariah
Poster
Tue 1:00 PDE-Driven Spatiotemporal Disentanglement
Jérémie DONA, Jean-Yves Franceschi, sylvain lamprier, patrick gallinari
Poster
Tue 1:00 Generalized Multimodal ELBO
Thomas Sutter, Imant Daunhawer, Julia E Vogt
Poster
Tue 1:00 Bayesian Context Aggregation for Neural Processes
Michael Volpp, Fabian Flürenbrock, Lukas Grossberger, Christian Daniel, Gerhard Neumann
Poster
Tue 1:00 Learning the Pareto Front with Hypernetworks
Aviv Navon, Aviv Shamsian, Ethan Fetaya, Gal Chechik
Poster
Tue 1:00 Hyperbolic Neural Networks++
Ryohei Shimizu, YUSUKE Mukuta, Tatsuya Harada
Oral
Tue 4:23 Scalable Learning and MAP Inference for Nonsymmetric Determinantal Point Processes
Mike Gartrell, Insu Han, Elvis Dohmatob, Jennifer Gillenwater, Victor-Emmanuel Brunel
Tue 6:00 Lapsed Physicists Wine-and-Cheese (#1)
Poster
Tue 9:00 Direction Matters: On the Implicit Bias of Stochastic Gradient Descent with Moderate Learning Rate
Jingfeng Wu, Difan Zou, vladimir braverman, Quanquan Gu
Poster
Tue 9:00 Robust Pruning at Initialization
Soufiane Hayou, Jean-Francois Ton, Arnaud Doucet, Yee Whye Teh
Poster
Tue 9:00 Statistical inference for individual fairness
Subha Maity, Songkai Xue, Mikhail Yurochkin, Yuekai Sun
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 Learning Parametrised Graph Shift Operators
George Dasoulas, Johannes Lutzeyer, Michalis Vazirgiannis
Poster
Tue 9:00 Sharper Generalization Bounds for Learning with Gradient-dominated Objective Functions
Yunwen Lei, Yiming Ying
Poster
Tue 9:00 FairBatch: Batch Selection for Model Fairness
Yuji Roh, Kangwook Lee, Steven Whang, Changho Suh
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 Large Associative Memory Problem in Neurobiology and Machine Learning
Dmitry Krotov, John J Hopfield
Poster
Tue 9:00 On the mapping between Hopfield networks and Restricted Boltzmann Machines
Matthew Smart, Anton Zilman
Poster
Tue 9:00 Learning a Latent Search Space for Routing Problems using Variational Autoencoders
André Hottung, Bhanu Bhandari, Kevin Tierney
Oral
Tue 11:00 Iterated learning for emergent systematicity in VQA
Ankit Vani, Max Schwarzer, Yuchen Lu, Eeshan Dhekane, Aaron Courville
Oral
Tue 12:00 Randomized Automatic Differentiation
Deniz Oktay, Nick McGreivy, Joshua Aduol, Alex Beatson, Ryan P Adams
Spotlight
Tue 12:50 Learning from Protein Structure with Geometric Vector Perceptrons
Bowen Jing, Stephan Eismann, Patricia Suriana, Raphael J Townshend, Ron Dror
Oral
Tue 13:13 On the mapping between Hopfield networks and Restricted Boltzmann Machines
Matthew Smart, Anton Zilman
Expo Talk Panel
Tue 14:00 Interpretability with skeptical and user-centric mind
Been Kim
Poster
Tue 17:00 Dataset Inference: Ownership Resolution in Machine Learning
Pratyush Maini, Mohammad Yaghini, Nicolas Papernot
Poster
Tue 17:00 Information Laundering for Model Privacy
Xinran Wang, Yu Xiang, Jun Gao, Jie Ding
Poster
Tue 17:00 Achieving Linear Speedup with Partial Worker Participation in Non-IID Federated Learning
Haibo Yang, Minghong Fang, Jia Liu
Poster
Tue 17:00 Monotonic Kronecker-Factored Lattice
William Bakst, Nobuyuki Morioka, Erez Louidor
Poster
Tue 17:00 Knowledge Distillation as Semiparametric Inference
Tri Dao, Govinda Kamath, Vasilis Syrgkanis, Lester Mackey
Poster
Tue 17:00 Generating Adversarial Computer Programs using Optimized Obfuscations
Shashank Srikant, Sijia Liu, Tamara Mitrovska, Shiyu Chang, Quanfu Fan, Gaoyuan Zhang, Una-May O'Reilly
Poster
Tue 17:00 Are Neural Rankers still Outperformed by Gradient Boosted Decision Trees?
Zhen Qin, Le Yan, Honglei Zhuang, Yi Tay, Rama Kumar Pasumarthi, Xuanhui Wang, Michael Bendersky, Marc Najork
Poster
Tue 17:00 RMSprop converges with proper hyper-parameter
Naichen Shi, Dawei Li, Mingyi Hong, Ruoyu Sun
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 20:30 Individually Fair Gradient Boosting
Alexander Vargo, Fan Zhang, Mikhail Yurochkin, Yuekai Sun
Spotlight
Tue 20:40 Are Neural Rankers still Outperformed by Gradient Boosted Decision Trees?
Zhen Qin, Le Yan, Honglei Zhuang, Yi Tay, Rama Kumar Pasumarthi, Xuanhui Wang, Michael Bendersky, Marc Najork
Oral
Tue 21:18 MONGOOSE: A Learnable LSH Framework for Efficient Neural Network Training
Beidi Chen, Zichang Liu, Binghui Peng, Zhaozhuo Xu, Jonathan L Li, Tri Dao, Zhao Song, Anshumali Shrivastava, Christopher Re
Invited Talk
Wed 0:00 Perceiving the 3D World from Images and Video
Lourdes Agapito
Poster
Wed 1:00 Dance Revolution: Long-Term Dance Generation with Music via Curriculum Learning
Ruozi Huang, Huang Hu, Wei Wu, Kei Sawada, Mi Zhang, Daxin Jiang
Poster
Wed 1:00 New Bounds For Distributed Mean Estimation and Variance Reduction
Peter Davies, Vijaykrishna Gurunathan, Niusha Moshrefi, Saleh Ashkboos, Dan Alistarh
Poster
Wed 1:00 Deep Neural Network Fingerprinting by Conferrable Adversarial Examples
Nils Lukas, Yuxuan Zhang, Florian Kerschbaum
Poster
Wed 1:00 Byzantine-Resilient Non-Convex Stochastic Gradient Descent
Zeyuan Allen-Zhu, Faeze Ebrahimianghazani, Jerry Li, Dan Alistarh
Poster
Wed 1:00 Geometry-aware Instance-reweighted Adversarial Training
Jingfeng Zhang, Jianing ZHU, Gang Niu, Bo Han, Masashi Sugiyama, Mohan Kankanhalli
Poster
Wed 1:00 A Better Alternative to Error Feedback for Communication-Efficient Distributed Learning
Samuel Horváth, Peter Richtarik
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 4:20 Influence Estimation for Generative Adversarial Networks
Naoyuki Terashita, Hiroki Ohashi, Yuichi Nonaka, Takashi Kanemaru
Spotlight
Wed 4:40 Deep Neural Network Fingerprinting by Conferrable Adversarial Examples
Nils Lukas, Yuxuan Zhang, Florian Kerschbaum
Invited Talk
Wed 8:00 Is My Dataset Biased?
Kate Saenko
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 Iterated learning for emergent systematicity in VQA
Ankit Vani, Max Schwarzer, Yuchen Lu, Eeshan Dhekane, Aaron Courville
Poster
Wed 9:00 Boost then Convolve: Gradient Boosting Meets Graph Neural Networks
Sergei Ivanov, Liudmila Prokhorenkova
Poster
Wed 9:00 IsarStep: a Benchmark for High-level Mathematical Reasoning
Wenda Li, Lei Yu, Yuhuai Wu, Lawrence Paulson
Poster
Wed 9:00 Geometry-Aware Gradient Algorithms for Neural Architecture Search
Liam Li, Misha Khodak, Nina Balcan, Ameet Talwalkar
Poster
Wed 9:00 More or Less: When and How to Build Convolutional Neural Network Ensembles
Abdul Wasay, Stratos Idreos
Poster
Wed 9:00 Modeling the Second Player in Distributionally Robust Optimization
Paul Michel, Tatsunori Hashimoto, Graham Neubig
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 Few-Shot Bayesian Optimization with Deep Kernel Surrogates
Martin Wistuba, Josif Grabocka
Poster
Wed 9:00 Theoretical bounds on estimation error for meta-learning
James Lucas, Mengye Ren, Irene Raissa KAMENI KAMENI, Toniann Pitassi, Richard Zemel
Poster
Wed 9:00 Learning Task-General Representations with Generative Neuro-Symbolic Modeling
Reuben Feinman, Brenden Lake
Wed 12:00 Women in Artificial Intelligence & Machine Learning (WinAIML)
Spotlight
Wed 12:48 LambdaNetworks: Modeling long-range Interactions without Attention
Irwan Bello
Spotlight
Wed 13:58 Differentially Private Learning Needs Better Features (or Much More Data)
Florian Tramer, Dan Boneh
Poster
Wed 17:00 Estimating Lipschitz constants of monotone deep equilibrium models
Chirag Pabbaraju, Ezra Winston, Zico Kolter
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 AutoLRS: Automatic Learning-Rate Schedule by Bayesian Optimization on the Fly
Yuchen Jin, Tianyi Zhou, Liangyu Zhao, Yibo Zhu, Chuanxiong Guo, Marco Canini, Arvind Krishnamurthy
Poster
Wed 17:00 Individually Fair Gradient Boosting
Alexander Vargo, Fan Zhang, Mikhail Yurochkin, Yuekai Sun
Poster
Wed 17:00 Influence Functions in Deep Learning Are Fragile
Samyadeep Basu, Phil Pope, Soheil Feizi
Poster
Wed 17:00 Interactive Weak Supervision: Learning Useful Heuristics for Data Labeling
Benedikt Boecking, Willie Neiswanger, Eric P Xing, Artur Dubrawski
Poster
Wed 17:00 Learning and Evaluating Representations for Deep One-Class Classification
Kihyuk Sohn, Chun-Liang Li, Jinsung Yoon, Minho Jin, Tomas Pfister
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 Combining Physics and Machine Learning for Network Flow Estimation
Arlei Lopes da Silva, Furkan Kocayusufoglu, Saber Jafarpour, Francesco Bullo, Ananthram Swami, Ambuj K Singh
Spotlight
Wed 20:40 Undistillable: Making A Nasty Teacher That CANNOT teach students
Haoyu Ma, Tianlong Chen, Ting-Kuei Hu, Chenyu You, Xiaohui Xie, Zhangyang Wang
Poster
Thu 1:00 Mind the Gap when Conditioning Amortised Inference in Sequential Latent-Variable Models
Justin Bayer, Maximilian Soelch, Atanas Mirchev, Baris Kayalibay, Patrick van der Smagt
Poster
Thu 1:00 Genetic Soft Updates for Policy Evolution in Deep Reinforcement Learning
Enrico Marchesini, Davide Corsi, Alessandro Farinelli
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 GShard: Scaling Giant Models with Conditional Computation and Automatic Sharding
Dmitry Lepikhin, HyoukJoong Lee, Yuanzhong Xu, Dehao Chen, Orhan Firat, Yanping Huang, Maxim Krikun, Noam Shazeer, Zhifeng Chen
Poster
Thu 1:00 Influence Estimation for Generative Adversarial Networks
Naoyuki Terashita, Hiroki Ohashi, Yuichi Nonaka, Takashi Kanemaru
Poster
Thu 1:00 Private Image Reconstruction from System Side Channels Using Generative Models
Yuanyuan Yuan, Shuai Wang, Junping Zhang
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 Do not Let Privacy Overbill Utility: Gradient Embedding Perturbation for Private Learning
Da Yu, Huishuai Zhang, Wei Chen, Tie-Yan Liu
Poster
Thu 1:00 Hopfield Networks is All You Need
Hubert Ramsauer, Bernhard Schäfl, Johannes Lehner, Philipp Seidl, Michael Widrich, Lukas Gruber, Markus Holzleitner, Thomas Adler, David Kreil, Michael K Kopp, Günter Klambauer, Johannes Brandstetter, Sepp Hochreiter
Poster
Thu 1:00 Learning Neural Generative Dynamics for Molecular Conformation Generation
Minkai Xu, Shitong Luo, Yoshua Bengio, Jian Peng, Jian Tang
Poster
Thu 1:00 Scalable Learning and MAP Inference for Nonsymmetric Determinantal Point Processes
Mike Gartrell, Insu Han, Elvis Dohmatob, Jennifer Gillenwater, Victor-Emmanuel Brunel
Poster
Thu 1:00 Conditional Generative Modeling via Learning the Latent Space
Sameera Ramasinghe, Kanchana Ranasinghe, Salman Khan, Nick Barnes, Stephen Gould
Spotlight
Thu 4:35 Unlearnable Examples: Making Personal Data Unexploitable
Hanxun Huang, Daniel Ma, Sarah Erfani, James Bailey, Yisen Wang
Thu 9:00 Machine Learning for Software Engineering
Poster
Thu 9:00 Bayesian Few-Shot Classification with One-vs-Each Pólya-Gamma Augmented Gaussian Processes
Jake Snell, Richard Zemel
Poster
Thu 9:00 CaPC Learning: Confidential and Private Collaborative Learning
Christopher Choquette-Choo, Natalie Dullerud, Adam Dziedzic, Yunxiang Zhang, Somesh Jha, Nicolas Papernot, Xiao Wang
Poster
Thu 9:00 Dataset Meta-Learning from Kernel Ridge-Regression
Timothy Nguyen, Zhourong Chen, Jaehoon Lee
Poster
Thu 9:00 Noise or Signal: The Role of Image Backgrounds in Object Recognition
Kai Xiao, Logan Engstrom, Andrew Ilyas, Aleksander Madry
Poster
Thu 9:00 Private Post-GAN Boosting
Marcel Neunhoeffer, Steven Wu, Cynthia Dwork
Poster
Thu 9:00 Differentially Private Learning Needs Better Features (or Much More Data)
Florian Tramer, Dan Boneh
Poster
Thu 9:00 Domain-Robust Visual Imitation Learning with Mutual Information Constraints
Edoardo Cetin, Oya Celiktutan
Poster
Thu 9:00 Dataset Condensation with Gradient Matching
Bo ZHAO, Konda Reddy Mopuri, Hakan Bilen
Poster
Thu 9:00 Cut out the annotator, keep the cutout: better segmentation with weak supervision
Sarah Hooper, Michael Wornow, Ying Seah, Peter Kellman, Hui Xue, Frederic Sala, Curtis Langlotz, Christopher Re
Oral
Thu 11:15 SenSeI: Sensitive Set Invariance for Enforcing Individual Fairness
Mikhail Yurochkin, Yuekai Sun
Thu 12:00 Philosophy and AGI (#2)
Poster
Thu 17:00 Evaluation of Similarity-based Explanations
Kazuaki Hanawa, Sho Yokoi, Satoshi Hara, Kentaro Inui
Poster
Thu 17:00 Learning perturbation sets for robust machine learning
Eric Wong, Zico Kolter
Poster
Thu 17:00 Estimating and Evaluating Regression Predictive Uncertainty in Deep Object Detectors
Ali Harakeh, Steven L Waslander
Poster
Thu 17:00 Randomized Automatic Differentiation
Deniz Oktay, Nick McGreivy, Joshua Aduol, Alex Beatson, Ryan P Adams
Poster
Thu 17:00 A Learning Theoretic Perspective on Local Explainability
Jeffrey Li, Vaishnavh Nagarajan, Gregory Plumb, Ameet Talwalkar
Poster
Thu 17:00 Clustering-friendly Representation Learning via Instance Discrimination and Feature Decorrelation
Yaling Tao, Kentaro Takagi, Kouta Nakata
Poster
Thu 17:00 $i$-Mix: A Domain-Agnostic Strategy for Contrastive Representation Learning
Kibok Lee, Yian Zhu, Kihyuk Sohn, Chun-Liang Li, Jinwoo Shin, Honglak Lee
Poster
Thu 17:00 Greedy-GQ with Variance Reduction: Finite-time Analysis and Improved Complexity
Shaocong Ma, Ziyi Chen, Yi Zhou, Shaofeng Zou
Poster
Thu 17:00 Neural representation and generation for RNA secondary structures
Zichao Yan, Will Hamilton, Mathieu Blanchette
Poster
Thu 17:00 Nonseparable Symplectic Neural Networks
Shiying Xiong, Yunjin Tong, Xingzhe He, Shuqi Yang, Cheng Yang, Bo Zhu
Poster
Thu 17:00 HeteroFL: Computation and Communication Efficient Federated Learning for Heterogeneous Clients
Enmao Diao, Jie Ding, VAHID TAROKH
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
Thu 17:00 Lapsed Physicists Wine-and-Cheese (#2)
Spotlight
Thu 19:55 RMSprop converges with proper hyper-parameter
Naichen Shi, Dawei Li, Mingyi Hong, Ruoyu Sun
Workshop
Fri 2:30 Science and Engineering of Deep Learning
Levent Sagun, Caglar Gulcehre, Adriana Romero, Negar Rostamzadeh, Stefano Sarao Mannelli, Lenka Zdeborova, Samy Bengio
Workshop
Fri 2:45 Ideas for machine learning from psychology's reproducibility crisis
Samuel J Bell
Workshop
Fri 3:30 Neural Compression: From Information Theory to Applications
Stephan Mandt, Robert Bamler, Yingzhen Li, Christopher Schroers, Yang Yang, Max Welling, Taco Cohen
Workshop
Fri 5:00 Keynote 1: Warren Gross. Title: Stochastic Computing for Machine Learning towards an Intelligent Edge
Workshop
Fri 5:15 Beyond Static Papers: Rethinking How We Share Scientific Understanding in ML
Krishna Murthy Jatavallabhula, Bhairav Mehta, Tegan Maharaj, Amy Tabb, Khimya Khetarpal, Aditya Kusupati, Anna Rogers, Sara Hooker, Breandan Considine, Devi Parikh, Derek Nowrouzezahrai, Yoshua Bengio
Workshop
Fri 5:55 AI for Public Health
Bryan Wilder, Ioana Bica, Marie-Laure Charpignon, Emma Pierson
Workshop
Fri 6:00 Workshop on Neural Architecture Search
Arber Zela, Aaron Klein, Frank Hutter, Liam Li, Jan Hendrik Metzen, Jovita Lukasik
Workshop
Fri 6:18 Adversarial Data Augmentation Improves Unsupervised Machine Learning
Chia-Yi Hsu
Workshop
Fri 6:30 Break & Poster session 1
Workshop
Fri 6:45 Responsible AI (RAI)
Ahmad Beirami, Emily Black, Krishna Gummadi, Hoda Heidari, Baharan Mirzasoleiman, Meisam Razaviyayn, Joshua Williams
Workshop
Fri 7:00 2nd Workshop on Practical ML for Developing Countries: Learning Under Limited/low Resource Scenarios
Esube Bekele, Waheeda Saib, Timnit Gebru, Meareg Hailemariam, Vukosi Marivate, Judy Gichoya
Workshop
Fri 7:00 Workshop on Learning to Learn
Sarah Bechtle, Todor Davchev, Yevgen Chebotar, Timothy Hospedales, Franziska Meier
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 7:00 Neural Conversational AI: Bridging the Gap Between Research and Real World (NeuCAIR)
Ahmad Beirami, Asli Celikyilmaz, Yun-Nung Chen, Paul Crook, Orianna DeMasi, Stephen Roller, Chinnadhurai Sankar, Joao Sedoc, Zhou Yu
Workshop
Fri 7:00 Interpretable Recommender System With Heterogeneous Information: A Geometric Deep Learning Perspective
Yan Leng
Workshop
Fri 7:00 Synthetic Data Generation: Quality, Privacy, Bias
Sergul Aydore, Krishnaram Kenthapadi, Haipeng Chen, Edward Choi, Jamie Hayes, Mario Fritz, Rachel Cummings, Krishnaram Kenthapadi
Workshop
Fri 7:10 Invited Speaker Dan Roth - Natural Language Understanding with Incidental Supervision
Dan Roth
Workshop
Fri 7:10 "Can Machine Learning Revolutionize Healthcare? Synthetic Data may be the Answer" by Mihaela van der Schaar, UCLA
Mihaela van der Schaar
Workshop
Fri 7:55 ICLR 2021 Workshop on Embodied Multimodal Learning (EML)
Ruohan Gao, Andrew Owens, Dinesh Jayaraman, Yuke Zhu, Jiajun Wu, Kristen Grauman
Workshop
Fri 8:00 Robust and reliable machine learning in the real world
Di Jin, Eric Wong, Yonatan Belinkov, Kai-Wei Chang, Zhijing Jin, Yanjun Qi, Aditi Raghunathan, Tristan Naumann, Mohit Bansal
Workshop
Fri 8:30 Workshop on Distributed and Private Machine Learning
Fatemeh Mireshghallah, Praneeth Vepakomma, Ayush Chopra, Vivek Sharma, Abhishek Singh, Adam Smith, Ramesh Raskar, Gautam Kamath, Reza Shokri
Workshop
Fri 8:45 Machine Learning for Preventing and Combating Pandemics
Pengtao Xie, Xiaodan Liang, Jure Leskovec, Judy Wawira, Jeremy Weiss, Manuel Gomez Rodriguez, Madalina Fiterau, Yueyu Jiang, Leo Celi, Eric P Xing
Workshop
Fri 8:45 Opening Remarks
Workshop
Fri 8:45 Security and Safety in Machine Learning Systems
Xinyun Chen, Cihang Xie, Ali Shafahi, Bo Li, Ding Zhao, Tom Goldstein, Dawn Song
Workshop
Fri 8:50 PROBLEM AND SOLUTION DOCUMENTATION TEMPLATE FOR MACHINE LEARNING COMPETITIONS TO ENHANCE EXPLAINABILITY, REPRODUCIBILITY, AND COLLABORATION BETWEEN STAKEHOLDERS
Olubayo Hamzat
Fri 9:00 Starting/Transitioning your career in ML during a pandemic
Workshop
Fri 9:01 "Differentially Private Synthetic Data Generations Using Generative Adversarial Networks" by Jinsung Yoon, Google Cloud AI
Jinsung Yoon
Workshop
Fri 9:11 Bambara Language Dataset for Sentiment Analysis
chayma fourati
Workshop
Fri 9:30 Break & Poster session 2
Workshop
Fri 9:40 Inference Risks for Machine Learning
David Evans
Workshop
Fri 9:51 "Towards Financial Synthetic Data" by Manuela M. Veloso, J.P.Morgan, CMU
Manuela Veloso
Workshop
Fri 10:05 Q&A for Inference Risks for Machine Learning
Workshop
Fri 10:54 TenSEAL: A Library for Encrypted Tensor Operations Using Homomorphic Encryption
Ayoub Benaissa
Workshop
Fri 11:06 Smoothness Matrices Beat Smoothness Constants: Better Communication Compression Techniques for Distributed Optimization
Mher Safaryan, Filip Hanzely, Peter Richtarik
Workshop
Fri 11:45 Spotlight 9: George Zhang et al., Universal Rate-Distortion-Perception Representations for Lossy Compression
Workshop
Fri 11:52 DeepSMOTE: Deep Learning for Imbalanced Data
Bartosz Krawczyk
Workshop
Fri 12:15 A Better Bound Gives a Hundred Rounds: Enhanced Privacy Guarantees via f-Divergences
Lalitha Sankar
Workshop
Fri 12:51 "Ethical Considerations of Generative AI" by Emily Denton, Google’s Ethical AI team
Emily Denton
Workshop
Fri 13:07 Pervasive Label Errors in Test Sets Destabilize Machine Learning Benchmarks
Curtis G Northcutt
Workshop
Fri 14:01 Contributed Talk 3 - Pervasive Label Errors in Test Sets Destabilize Machine Learning Benchmarks
Curtis G Northcutt
Workshop
Fri 15:25 Invited Speaker Paroma Varma - Snorkel: Programmatically Labeling Training Data
Paroma Varma
Workshop
MPCLeague: Robust 4-party Computation for Privacy-Preserving Machine Learning
Nishat Koti, Arpita Patra, Ajith Suresh
Workshop
Smoothness Matrices Beat Smoothness Constants: Better Communication Compression Techniques for Distributed Optimization
Mher Safaryan, Filip Hanzely, Peter Richtarik
Workshop
Talk Less, Smile More: Reducing Communication with Distributed Auto-Differentiation
Bradley Baker, Vince Calhoun, Barak Pearlmutter, Sergey Plis
Workshop
Does Differential Privacy Defeat Data Poisoning?
Matthew Jagielski, Alina Oprea
Workshop
Differentially Private Multi-Task Learning
Shengyuan Hu, Steven Wu, Virginia Smith
Workshop
Prior-Free Auctions for the Demand Side of Federated Learning
Andreas Haupt, Vaikkunth Mugunthan
Workshop
SWIFT: Super-fast and Robust Privacy-Preserving Machine Learning
Nishat Koti, Mahak Pancholi, Arpita Patra, Ajith Suresh
Workshop
Privacy and Integrity Preserving Training Using Trusted Hardware
Seyedeh Hanieh Hashemi, Yongqin Wang, Murali Annavaram
Workshop
Membership Inference Attack on Graph Neural Networks
Iyiola Emmanuel Olatunji, Wolfgang Nejdl, Megha Khosla
Workshop
TenSEAL: A Library for Encrypted Tensor Operations Using Homomorphic Encryption
Ayoub Benaissa