Filter by Keyword:

188 Results

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 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 Noise against noise: stochastic label noise helps combat inherent label noise
Pengfei Chen, Guangyong Chen, Junjie Ye, jingwei zhao, Pheng-Ann Heng
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 Revisiting Locally Supervised Learning: an Alternative to End-to-end Training
Yulin Wang, Zanlin Ni, Shiji Song, Le Yang, Gao Huang
Poster
Mon 1:00 Overfitting for Fun and Profit: Instance-Adaptive Data Compression
Ties van Rozendaal, Iris Huijben, Taco Cohen
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 Wasserstein-2 Generative Networks
Alexander Korotin, Vage Egiazarian, Arip Asadulaev, Alexander Safin, Evgeny Burnaev
Poster
Mon 9:00 On the Stability of Fine-tuning BERT: Misconceptions, Explanations, and Strong Baselines
Marius Mosbach, Maksym Andriushchenko, Dietrich Klakow
Poster
Mon 9:00 Revisiting Few-sample BERT Fine-tuning
Tianyi Zhang, Felix Wu, Arzoo Katiyar, Kilian Weinberger, Yoav Artzi
Poster
Mon 9:00 Extracting Strong Policies for Robotics Tasks from Zero-Order Trajectory Optimizers
Cristina Pinneri, Shambhuraj Sawant, Sebastian Blaes, Georg Martius
Poster
Mon 9:00 Adaptive Federated Optimization
Sashank Reddi, Zachary Charles, Manzil Zaheer, Zachary Garrett, Keith Rush, Jakub Konečný, Sanjiv Kumar, Brendan McMahan
Poster
Mon 9:00 Fast convergence of stochastic subgradient method under interpolation
Huang Fang, Zhenan Fan, Michael Friedlander
Poster
Mon 9:00 Learning Hyperbolic Representations of Topological Features
Panagiotis Kyriakis, Iordanis Fostiropoulos, Paul Bogdan
Poster
Mon 9:00 On the Impossibility of Global Convergence in Multi-Loss Optimization
Alistair Letcher
Poster
Mon 9:00 Accelerating Convergence of Replica Exchange Stochastic Gradient MCMC via Variance Reduction
Wei Deng, Qi Feng, Georgios Karagiannis, Guang Lin, Faming Liang
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
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 11:30 Growing Efficient Deep Networks by Structured Continuous Sparsification
Xin Yuan, Pedro Savarese, Michael Maire
Spotlight
Mon 11:45 Geometry-Aware Gradient Algorithms for Neural Architecture Search
Liam Li, Misha Khodak, Nina Balcan, Ameet Talwalkar
Spotlight
Mon 12:15 On the Theory of Implicit Deep Learning: Global Convergence with Implicit Layers
Kenji Kawaguchi
Spotlight
Mon 12:25 Sharpness-aware Minimization for Efficiently Improving Generalization
Pierre Foret, Ariel Kleiner, Hossein Mobahi, Behnam Neyshabur
Spotlight
Mon 13:40 Gradient Vaccine: Investigating and Improving Multi-task Optimization in Massively Multilingual Models
Zirui Wang, Yulia Tsvetkov, Orhan Firat, Yuan Cao
Poster
Mon 17:00 Offline Model-Based Optimization via Normalized Maximum Likelihood Estimation
Justin Fu, Sergey Levine
Poster
Mon 17:00 Learning A Minimax Optimizer: A Pilot Study
Jiayi Shen, Xiaohan Chen, Howard Heaton, Tianlong Chen, Jialin Liu, Wotao Yin, Zhangyang Wang
Poster
Mon 17:00 The Deep Bootstrap Framework: Good Online Learners are Good Offline Generalizers
Preetum Nakkiran, Behnam Neyshabur, Hanie Sedghi
Poster
Mon 17:00 Personalized Federated Learning with First Order Model Optimization
Michael Zhang, Karan Sapra, Sanja Fidler, Serena Yeung, Jose M. Alvarez
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 Why resampling outperforms reweighting for correcting sampling bias with stochastic gradients
Jing An, Lexing Ying, Yuhua Zhu
Poster
Mon 17:00 Sequential Density Ratio Estimation for Simultaneous Optimization of Speed and Accuracy
Akinori Ebihara, Taiki Miyagawa, Kazuyuki Sakurai, Hitoshi Imaoka
Poster
Mon 17:00 Partitioned Learned Bloom Filters
Kapil Vaidya, Eric Knorr, Michael Mitzenmacher, Tim Kraska
Poster
Mon 17:00 Tilted Empirical Risk Minimization
Tian Li, Ahmad Beirami, Maziar Sanjabi, Virginia Smith
Poster
Mon 17:00 Proximal Gradient Descent-Ascent: Variable Convergence under KŁ Geometry
Ziyi Chen, Yi Zhou, Tengyu Xu, Yingbin Liang
Poster
Mon 17:00 When does preconditioning help or hurt generalization?
Shun-ichi Amari, Jimmy Ba, Roger Grosse, Chen Li, Atsushi Nitanda, Taiji Suzuki, Denny Wu, Ji Xu
Poster
Mon 17:00 PlasticineLab: A Soft-Body Manipulation Benchmark with Differentiable Physics
Zhiao Huang, Yuanming Hu, Tao Du, Siyuan Zhou, Hao Su, Joshua B Tenenbaum, Chuang Gan
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 Regularization Matters in Policy Optimization - An Empirical Study on Continuous Control
Zhuang Liu, Xuanlin Li, Bingyi Kang, trevor darrell
Poster
Mon 17:00 Meta-Learning with Neural Tangent Kernels
Yufan Zhou, Zhenyi Wang, Jiayi Xian, Changyou Chen, Jinhui Xu
Poster
Mon 17:00 The Role of Momentum Parameters in the Optimal Convergence of Adaptive Polyak's Heavy-ball Methods
Wei Tao, sheng long, Gaowei Wu, Qing Tao
Poster
Mon 17:00 Rethinking Architecture Selection in Differentiable NAS
Ruochen Wang, Minhao Cheng, Xiangning Chen, Xiaocheng Tang, Cho-Jui Hsieh
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 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 Sample-Efficient Automated Deep Reinforcement Learning
Jörg Franke, Gregor Koehler, André Biedenkapp, Frank Hutter
Poster
Tue 1:00 Generalized Energy Based Models
Michael Arbel, Liang Zhou, Arthur Gretton
Poster
Tue 1:00 Coping with Label Shift via Distributionally Robust Optimisation
Jingzhao Zhang, Aditya Krishna Menon, Andreas Veit, Srinadh Bhojanapalli, Sanjiv Kumar, Suvrit Sra
Poster
Tue 1:00 Efficient Certified Defenses Against Patch Attacks on Image Classifiers
Jan Hendrik Metzen, Maksym Yatsura
Poster
Tue 1:00 Learning the Pareto Front with Hypernetworks
Aviv Navon, Aviv Shamsian, Ethan Fetaya, Gal Chechik
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
Spotlight
Tue 4:48 Noise against noise: stochastic label noise helps combat inherent label noise
Pengfei Chen, Guangyong Chen, Junjie Ye, jingwei zhao, Pheng-Ann Heng
Spotlight
Tue 5:38 Fidelity-based Deep Adiabatic Scheduling
Eli Ovits, Lior Wolf
Invited Talk
Tue 8:00 AI in Finance: Scope and Examples
Manuela Veloso
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 Taming GANs with Lookahead-Minmax
Tatjana Chavdarova, Matteo Pagliardini, Sebastian Stich, François Fleuret, Martin Jaggi
Poster
Tue 9:00 FairBatch: Batch Selection for Model Fairness
Yuji Roh, Kangwook Lee, Steven Whang, Changho Suh
Poster
Tue 9:00 Quantifying Differences in Reward Functions
Adam Gleave, Michael Dennis, Shane Legg, Stuart Russell, Jan Leike
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 Understanding Over-parameterization in Generative Adversarial Networks
Yogesh Balaji, Mohammadmahdi Sajedi, Neha Kalibhat, Mucong Ding, Dominik Stöger, Mahdi Soltanolkotabi, Soheil Feizi
Poster
Tue 9:00 Learning a Latent Search Space for Routing Problems using Variational Autoencoders
André Hottung, Bhanu Bhandari, Kevin Tierney
Poster
Tue 9:00 Clairvoyance: A Pipeline Toolkit for Medical Time Series
Dan Jarrett, Jinsung Yoon, Ioana Bica, Zhaozhi Qian, Ari Ercole, Mihaela van der Schaar
Poster
Tue 9:00 Tent: Fully Test-Time Adaptation by Entropy Minimization
Dequan Wang, Evan Shelhamer, Shaoteng Liu, Bruno Olshausen, trevor darrell
Poster
Tue 9:00 UMEC: Unified model and embedding compression for efficient recommendation systems
Jiayi Shen, Haotao Wang, Shupeng Gui, Jianchao Tan, Zhangyang Wang, Ji Liu
Poster
Tue 9:00 DC3: A learning method for optimization with hard constraints
Priya Donti, David Rolnick, Zico Kolter
Poster
Tue 9:00 Text Generation by Learning from Demonstrations
Richard Pang, He He
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 Auction Learning as a Two-Player Game
Jad Rahme, Samy Jelassi, S. M Weinberg
Poster
Tue 9:00 On the Origin of Implicit Regularization in Stochastic Gradient Descent
Samuel Smith, Benoit Dherin, David Barrett, Soham De
Poster
Tue 9:00 Single-Timescale Actor-Critic Provably Finds Globally Optimal Policy
Zuyue Fu, Zhuoran Yang, Zhaoran Wang
Poster
Tue 9:00 Sharper Generalization Bounds for Learning with Gradient-dominated Objective Functions
Yunwen Lei, Yiming Ying
Poster
Tue 9:00 On the Theory of Implicit Deep Learning: Global Convergence with Implicit Layers
Kenji Kawaguchi
Oral
Tue 12:00 Randomized Automatic Differentiation
Deniz Oktay, Nick McGreivy, Joshua Aduol, Alex Beatson, Ryan P Adams
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
Poster
Tue 17:00 Discovering Non-monotonic Autoregressive Orderings with Variational Inference
Xuanlin Li, Brandon Trabucco, Dong Huk Park, Michael Luo, Sheng Shen, trevor darrell, Yang Gao
Poster
Tue 17:00 Autoregressive Dynamics Models for Offline Policy Evaluation and Optimization
Michael Zhang, Tom Paine, Ofir Nachum, Cosmin Paduraru, George Tucker, ziyu wang, Mohammad Norouzi
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 DDPNOpt: Differential Dynamic Programming Neural Optimizer
Guan-Horng Liu, Tianrong Chen, Evangelos Theodorou
Poster
Tue 17:00 A Hypergradient Approach to Robust Regression without Correspondence
Yujia Xie, Yixiu Mao, Simiao Zuo, Hongteng Xu, Xiaojing Ye, Tuo Zhao, Hongyuan Zha
Poster
Tue 17:00 Memory Optimization for Deep Networks
Aashaka Shah, Chao-Yuan Wu, Jayashree Mohan, Vijay Chidambaram, Philipp Krähenbühl
Poster
Tue 17:00 Large Batch Simulation for Deep Reinforcement Learning
Brennan Shacklett, Erik Wijmans, Aleksei Petrenko, Manolis Savva, Dhruv Batra, Vladlen Koltun, Kayvon Fatahalian
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 Implicit Under-Parameterization Inhibits Data-Efficient Deep Reinforcement Learning
Aviral Kumar, Rishabh Agarwal, Dibya Ghosh, Sergey Levine
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 Fantastic Four: Differentiable and Efficient Bounds on Singular Values of Convolution Layers
ssingla Singla, Soheil Feizi
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 The Importance of Pessimism in Fixed-Dataset Policy Optimization
Jacob Buckman, Carles Gelada, Marc G Bellemare
Poster
Tue 17:00 Understanding the role of importance weighting for deep learning
Da Xu, Yuting Ye, Chuanwei Ruan
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 RNNLogic: Learning Logic Rules for Reasoning on Knowledge Graphs
Meng Qu, Junkun Chen, Louis-Pascal A Xhonneux, Yoshua Bengio, Jian Tang
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
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 21:43 Memory Optimization for Deep Networks
Aashaka Shah, Chao-Yuan Wu, Jayashree Mohan, Vijay Chidambaram, Philipp Krähenbühl
Invited Talk
Wed 0:00 Perceiving the 3D World from Images and Video
Lourdes Agapito
Poster
Wed 1:00 Byzantine-Resilient Non-Convex Stochastic Gradient Descent
Zeyuan Allen-Zhu, Faeze Ebrahimianghazani, Jerry Li, Dan Alistarh
Poster
Wed 1:00 Deployment-Efficient Reinforcement Learning via Model-Based Offline Optimization
Tatsuya Matsushima, Hiroki Furuta, Yutaka Matsuo, Ofir Nachum, Shixiang Gu
Poster
Wed 1:00 A Better Alternative to Error Feedback for Communication-Efficient Distributed Learning
Samuel Horváth, Peter Richtarik
Poster
Wed 1:00 Fidelity-based Deep Adiabatic Scheduling
Eli Ovits, Lior Wolf
Poster
Wed 1:00 Differentiable Segmentation of Sequences
Erik Scharwächter, Jonathan Lennartz, Emmanuel Müller
Spotlight
Wed 5:25 Tent: Fully Test-Time Adaptation by Entropy Minimization
Dequan Wang, Evan Shelhamer, Shaoteng Liu, Bruno Olshausen, trevor darrell
Poster
Wed 9:00 Modeling the Second Player in Distributionally Robust Optimization
Paul Michel, Tatsunori Hashimoto, Graham Neubig
Poster
Wed 9:00 Differentiable Trust Region Layers for Deep Reinforcement Learning
Fabian Otto, Philipp Becker, Vien A Ngo, Hanna Ziesche, Gerhard Neumann
Poster
Wed 9:00 Boost then Convolve: Gradient Boosting Meets Graph Neural Networks
Sergei Ivanov, Liudmila Prokhorenkova
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 Sharpness-aware Minimization for Efficiently Improving Generalization
Pierre Foret, Ariel Kleiner, Hossein Mobahi, Behnam Neyshabur
Poster
Wed 9:00 Growing Efficient Deep Networks by Structured Continuous Sparsification
Xin Yuan, Pedro Savarese, Michael Maire
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 Few-Shot Bayesian Optimization with Deep Kernel Surrogates
Martin Wistuba, Josif Grabocka
Poster
Wed 9:00 Continuous Wasserstein-2 Barycenter Estimation without Minimax Optimization
Alexander Korotin, Lingxiao Li, Justin Solomon, Evgeny Burnaev
Poster
Wed 9:00 Federated Learning via Posterior Averaging: A New Perspective and Practical Algorithms
Maruan Al-Shedivat, Jennifer Gillenwater, Eric P Xing, Afshin Rostamizadeh
Poster
Wed 9:00 OPAL: Offline Primitive Discovery for Accelerating Offline Reinforcement Learning
Anurag Ajay, Aviral Kumar, Pulkit Agrawal, Sergey Levine, Ofir Nachum
Poster
Wed 9:00 HyperDynamics: Meta-Learning Object and Agent Dynamics with Hypernetworks
Zhou Xian, Shamit Lal, Hsiao-Yu Tung, Anthony Platanios, Katerina Fragkiadaki
Poster
Wed 9:00 Geometry-Aware Gradient Algorithms for Neural Architecture Search
Liam Li, Misha Khodak, Nina Balcan, Ameet Talwalkar
Spotlight
Wed 12:38 Sequential Density Ratio Estimation for Simultaneous Optimization of Speed and Accuracy
Akinori Ebihara, Taiki Miyagawa, Kazuyuki Sakurai, Hitoshi Imaoka
Poster
Wed 17:00 A Geometric Analysis of Deep Generative Image Models and Its Applications
Binxu Wang, Carlos Ponce
Poster
Wed 17:00 Modelling Hierarchical Structure between Dialogue Policy and Natural Language Generator with Option Framework for Task-oriented Dialogue System
Jianhong Wang, Yuan Zhang, Tae-Kyun Kim, Yunjie Gu
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 Is Attention Better Than Matrix Decomposition?
Zhengyang Geng, Meng-Hao Guo, Hongxu Chen, Xia Li, Ke Wei, Zhouchen Lin
Poster
Wed 17:00 Revisiting Dynamic Convolution via Matrix Decomposition
Yunsheng Li, Yinpeng Chen, Xiyang Dai, mengchen liu, Dongdong Chen, Ye Yu, Lu Yuan, Zicheng Liu, Mei Chen, Nuno Vasconcelos
Poster
Wed 17:00 Task-Agnostic Morphology Evolution
Donald Hejna III, Pieter Abbeel, Lerrel Pinto
Poster
Wed 17:00 Efficient Empowerment Estimation for Unsupervised Stabilization
Ruihan Zhao, Kevin Lu, Pieter Abbeel, Stas Tiomkin
Poster
Wed 17:00 Efficient Wasserstein Natural Gradients for Reinforcement Learning
Ted Moskovitz, Michael Arbel, Ferenc Huszar, Arthur Gretton
Poster
Wed 17:00 Economic Hyperparameter Optimization With Blended Search Strategy
Chi Wang, Qingyun Wu, Silu Huang, Amin Saied
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 19:15 GAN "Steerability" without optimization
Nurit Spingarn Eliezer, Ron Banner, Tomer Michaeli
Spotlight
Wed 20:20 Understanding the role of importance weighting for deep learning
Da Xu, Yuting Ye, Chuanwei Ruan
Spotlight
Wed 20:50 CPT: Efficient Deep Neural Network Training via Cyclic Precision
Yonggan Fu, Han Guo, Meng Li, Xin Yang, Yining Ding, Vikas Chandra, Yingyan Lin
Spotlight
Wed 21:15 PlasticineLab: A Soft-Body Manipulation Benchmark with Differentiable Physics
Zhiao Huang, Yuanming Hu, Tao Du, Siyuan Zhou, Hao Su, Joshua B Tenenbaum, Chuang Gan
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 0:00 Rethinking Architecture Selection in Differentiable NAS
Ruochen Wang, Minhao Cheng, Xiangning Chen, Xiaocheng Tang, Cho-Jui Hsieh
Poster
Thu 1:00 Understanding the effects of data parallelism and sparsity on neural network training
Namhoon Lee, Thalaiyasingam Ajanthan, Philip Torr, Martin Jaggi
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 Loss Function Discovery for Object Detection via Convergence-Simulation Driven Search
Peidong Liu, Gengwei Zhang, Bochao Wang, Hang Xu, Xiaodan Liang, Yong Jiang, Zhenguo Li
Poster
Thu 1:00 Adaptive Extra-Gradient Methods for Min-Max Optimization and Games
Kimon ANTONAKOPOULOS, E. Belmega, Panayotis Mertikopoulos
Poster
Thu 1:00 GAN "Steerability" without optimization
Nurit Spingarn Eliezer, Ron Banner, Tomer Michaeli
Poster
Thu 1:00 Representation Balancing Offline Model-based Reinforcement Learning
Byung-Jun Lee, Jongmin Lee, Kee-Eung Kim
Poster
Thu 1:00 Categorical Normalizing Flows via Continuous Transformations
Phillip Lippe, Stratis Gavves
Poster
Thu 1:00 ChipNet: Budget-Aware Pruning with Heaviside Continuous Approximations
Rishabh Tiwari, Udbhav Bamba, Arnav Chavan, Deepak Gupta
Poster
Thu 1:00 Repurposing Pretrained Models for Robust Out-of-domain Few-Shot Learning
Namyeong Kwon, Hwidong Na, Gabriel Huang, Simon Lacoste-Julien
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 R-GAP: Recursive Gradient Attack on Privacy
Junyi Zhu, Matthew Blaschko
Poster
Thu 1:00 A Diffusion Theory For Deep Learning Dynamics: Stochastic Gradient Descent Exponentially Favors Flat Minima
Zeke Xie, Issei Sato, Masashi Sugiyama
Spotlight
Thu 3:35 Quantifying Differences in Reward Functions
Adam Gleave, Michael Dennis, Shane Legg, Stuart Russell, Jan Leike
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 BSQ: Exploring Bit-Level Sparsity for Mixed-Precision Neural Network Quantization
Huanrui Yang, Lin Duan, Yiran Chen, Hai Li
Poster
Thu 9:00 Blending MPC & Value Function Approximation for Efficient Reinforcement Learning
Mohak Bhardwaj, Sanjiban Choudhury, Byron Boots
Poster
Thu 9:00 Enforcing robust control guarantees within neural network policies
Priya Donti, Melrose Roderick, Mahyar Fazlyab, Zico Kolter
Poster
Thu 9:00 Initialization and Regularization of Factorized Neural Layers
Misha Khodak, Neil Tenenholtz, Lester Mackey, Nicolo Fusi
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 Linear Last-iterate Convergence in Constrained Saddle-point Optimization
Chen-Yu Wei, Chung-Wei Lee, Mengxiao Zhang, Haipeng Luo
Poster
Thu 9:00 Local Search Algorithms for Rank-Constrained Convex Optimization
Kyriakos Axiotis, Maxim Sviridenko
Poster
Thu 9:00 Gradient Vaccine: Investigating and Improving Multi-task Optimization in Massively Multilingual Models
Zirui Wang, Yulia Tsvetkov, Orhan Firat, Yuan Cao
Oral
Thu 11:30 When Do Curricula Work?
Xiaoxia (Shirley) Wu, Ethan Dyer, Behnam Neyshabur
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 Learning to Make Decisions via Submodular Regularization
Ayya Alieva, Aiden Aceves, Jialin Song, Stephen Mayo, Yisong Yue, Yuxin Chen
Poster
Thu 17:00 Convex Regularization behind Neural Reconstruction
Arda Sahiner, Morteza Mardani, Batu Ozturkler, Mert Pilanci, John M Pauly
Poster
Thu 17:00 Randomized Automatic Differentiation
Deniz Oktay, Nick McGreivy, Joshua Aduol, Alex Beatson, Ryan P Adams
Poster
Thu 17:00 Linear Convergent Decentralized Optimization with Compression
Xiaorui Liu, Yao Li, Rongrong Wang, Jiliang Tang, Ming Yan
Poster
Thu 17:00 CPT: Efficient Deep Neural Network Training via Cyclic Precision
Yonggan Fu, Han Guo, Meng Li, Xin Yang, Yining Ding, Vikas Chandra, Yingyan Lin
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 Molecule Optimization by Explainable Evolution
Binghong Chen, Tianzhe Wang, Chengtao Li, Hanjun Dai, Le Song
Poster
Thu 17:00 Neural representation and generation for RNA secondary structures
Zichao Yan, Will Hamilton, Mathieu Blanchette
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 ANOCE: Analysis of Causal Effects with Multiple Mediators via Constrained Structural Learning
Hengrui Cai, Rui Song, Wenbin Lu
Poster
Thu 17:00 When Do Curricula Work?
Xiaoxia (Shirley) Wu, Ethan Dyer, Behnam Neyshabur
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 DynaTune: Dynamic Tensor Program Optimization in Deep Neural Network Compilation
Minjia Zhang, Menghao Li, Chi Wang, Mingqin Li
Poster
Thu 17:00 A Design Space Study for LISTA and Beyond
Tianjian Meng, Xiaohan Chen, Yifan Jiang, Zhangyang Wang
Poster
Thu 17:00 Non-asymptotic Confidence Intervals of Off-policy Evaluation: Primal and Dual Bounds
Yihao Feng, Ziyang Tang, Na Zhang, Qiang Liu
Poster
Thu 17:00 How Much Over-parameterization Is Sufficient to Learn Deep ReLU Networks?
Zixiang Chen, Yuan Cao, Difan Zou, Quanquan Gu
Workshop
Fri 5:10 Spotlight 2: Yibo Yang and Stephan Mandt, Lower Bounding Rate-Distortion From Samples
Workshop
Fri 6:30 Break & Poster session 1
Workshop
Fri 6:30 Data-Efficient Training of Autoencoders for Mildly Non-Linear Problems
Muhammad Al-Digeil
Workshop
Fri 7:04 Poster Spotlight "Overfitting in Bayesian Optimization: an empirical study and early-stopping solution"
Huibin Shen, Anastasia Makarova
Workshop
Fri 7:06 Poster Spotlight "Width transfer: on the (in)variance of width optimization"
Ting-Wu Chin
Workshop
Fri 8:40 Biased Client Selection for Improved Convergence of Federated Learning
Gauri Joshi
Workshop
Fri 8:57 Data-driven Weight Initialization with Sylvester Solvers
Buna Das
Workshop
Fri 9:30 Break & Poster session 2
Workshop
Fri 11:06 Smoothness Matrices Beat Smoothness Constants: Better Communication Compression Techniques for Distributed Optimization
Mher Safaryan, Filip Hanzely, Peter Richtarik
Workshop
Fri 12:15 A Bayesian Optimization Approach to Estimating Expected Match Time and Organ Quality in Kidney Exchange
Naveen Durvasula
Workshop
Fri 14:10 Improving Exploration in Policy Gradient Search: Application to Symbolic Optimization
Workshop
COMBO: Conservative Offline Model-Based Policy Optimization
Tianhe (Kevin) Yu, Aviral Kumar, Aravind Rajeswaran, Rafael Rafailov, Sergey Levine, Chelsea Finn
Workshop
OptiDICE: Offline Policy Optimization via Stationary Distribution Correction Estimation
Jongmin Lee, Wonseok Jeon, Byung-Jun Lee, Joelle Pineau, Kee-Eung Kim
Workshop
Gradient-Masked Federated Optimization
Irene Tenison, Sreya Francis, Irina Rish
Workshop
Bridging the Gap Between Adversarial Robustness and Optimization Bias
Fartash Faghri
Workshop
Federated Learning's Blessing: FedAvg has Linear Speedup
Zhaonan Qu, Kaixiang Lin, Zhaojian Li, Jiayu Zhou, Zhengyuan Zhou
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
Differentially Private Multi-Task Learning
Shengyuan Hu, Steven Wu, Virginia Smith
Workshop
Personalized Federated Learning: A Unified Framework and Universal Optimization Techniques
Filip Hanzely, Boxin Zhao, Mladen Kolar