Google AI Weblog: Google at NeurIPS 2021
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This week marks the start of the 35th annual Convention on Neural Data Processing Methods (NeurIPS 2021), the largest machine studying convention of the yr. NeurIPS 2021 shall be held nearly and consists of invited talks, demonstrations and shows of among the newest in machine studying analysis. This yr, NeurIPS additionally introduced a brand new Datasets and Benchmarks observe, which is able to embody publications, talks, posters, and discussions associated to this analysis space.
Google can have a robust presence with greater than 170 accepted papers, moreover contributing to and studying from the broader tutorial analysis group by way of talks, posters, workshops, and tutorials. You may study extra about our work being introduced within the checklist beneath (Google affiliations highlighted in daring).
Organizing Committee
Communications Co-Chair: Emily Denton
Program Co-Chair: Yann Dauphin
Workshop Co-Chair: Sanmi Koyejo
Senior Space Chairs: Alekh Agarwal, Amir Globerson, Been Kim, Charles Sutton, Claudio Gentile, Corinna Cortes, Dale Schuurmans, David Duvenaud, Elad Hazan, Hugo Larochelle, Jean-Philippe Vert, Kevin Murphy, Marco Cuturi, Mehryar Mohri, Mohammad Ghavamzadeh, Samory Kpotufe, Sanjiv Kumar, Satyen Kale, Sergey Levine, Tara N. Sainath, Yishay Mansour
Space Chairs: Abhishek Kumar, Abhradeep Guha Thakurta, Alex Kulesza, Alexander A. Alemi, Alexander T. Toshev, Amin Karbasi, Amit Daniely, Ananda Theertha Suresh, Ankit Singh Rawat, Ashok Cutkosky, Badih Ghazi, Balaji Lakshminarayanan, Ben Poole, Bo Dai, Boqing Gong, Chelsea Finn, Chiyuan Zhang, Christian Szegedy, Cordelia Schmid, Craig Boutilier, Cyrus Rashtchian, D. Sculley, Daniel Keysers, David Ha, Denny Zhou, Dilip Krishnan, Dumitru Erhan, Dustin Tran, Ekin Dogus Cubuk, Fabian Pedregosa, George Tucker, Hanie Sedghi, Hanjun Dai, Heinrich Jiang, Hossein Mobahi, Izhak Shafran, Jaehoon Lee, Jascha Sohl-Dickstein, Jasper Snoek, Jeffrey Pennington, Jelani Nelson, Jieming Mao, Justin Gilmer, Karol Hausman, Karthik Sridharan, Kevin Swersky, Maithra Raghu, Mario Lucic, Mathieu Blondel, Matt Kusner, Matthew Johnson, Matthieu Geist, Ming-Hsuan Yang, Mohammad Mahdian, Mohammad Norouzi, Nal Kalchbrenner, Naman Agarwal, Nicholas Carlini, Nicolas Papernot, Olivier Bachem, Olivier Pietquin, Paul Duetting, Praneeth Netrapalli, Pranjal Awasthi, Prateek Jain, Quentin Berthet, Renato Paes Leme, Richard Nock, Rif A. Saurous, Rose Yu, Roy Frostig, Samuel Stern Schoenholz, Sashank J. Reddi, Sercan O. Arik, Sergei Vassilvitskii, Sergey Ioffe, Shay Moran, Silvio Lattanzi, Simon Kornblith, Srinadh Bhojanapalli, Thang Luong, Thomas Steinke, Tim Salimans, Tomas Pfister, Tomer Koren, Uri Stemmer, Vahab Mirrokni, Vikas Sindhwani, Vincent Dumoulin, Virginia Smith, Vladimir Braverman, W. Ronny Huang, Wen Solar, Yang Li, Yasin Abbasi-Yadkori, Yinlam Chow,Yujia Li, Yunhe Wang, Zoltán Szabó
NeurIPS Basis Board 2021: Michael Mozer, Corinna Cortes, Hugo Larochelle, John C. Platt, Fernando Pereira
Check of Time Award
On-line Studying for Latent Dirichlet Allocation
Matthew D. Hoffman†, David M. Blei, Francis Bach
Publications
Deep Reinforcement Studying on the Fringe of the Statistical Precipice (see weblog publish)
Excellent Paper Award Recipient
Rishabh Agarwal, Max Schwarzer, Pablo Samuel Castro, Aaron Courville, Marc G. Bellemare
A Separation Outcome Between Information-Oblivious and Information-Conscious Poisoning Assaults
Samuel Deng, Sanjam Garg, Somesh Jha, Saeed Mahloujifar, Mohammad Mahmoody, Abhradeep Guha Thakurta
Adversarial Robustness of Streaming Algorithms By way of Significance Sampling
Vladimir Braverman, Avinatan Hassidim, Yossi Matias, Mariano Schain, Sandeep Silwal, Samson Zhou
Aligning Silhouette Topology for Self-Adaptive 3D Human Pose Restoration
Mugallodi Rakesh, Jogendra Nath Kundu, Varun Jampani, R. Venkatesh Babu
Consideration Bottlenecks for Multimodal Fusion
Arsha Nagrani, Shan Yang, Anurag Arnab, Aren Jansen, Cordelia Schmid, Chen Solar
Autonomous Reinforcement Studying by way of Subgoal Curricula
Archit Sharma, Abhishek Gupta, Sergey Levine, Karol Hausman, Chelsea Finn
Calibration and Consistency of Adversarial Surrogate Losses
Pranjal Awasthi, Natalie S. Frank, Anqi Mao, Mehryar Mohri, Yutao Zhong
Compressive Visible Representations
Kuang-Huei Lee, Anurag Arnab, Sergio Guadarrama, John Canny, Ian Fischer
Counterfactual Invariance to Spurious Correlations in Textual content Classification
Victor Veitch, Alexander D’Amour, Steve Yadlowsky, Jacob Eisenstein
Deep Studying By way of the Lens of Instance Issue
Robert J.N. Baldock, Hartmut Maennel, Behnam Neyshabur
Deep Neural Networks as Level Estimates for Deep Gaussian Processes
Vinent Dutordoir, James Hensman, Mark van der Wilk, Carl Henrik Ek, Zoubin Ghahramani, Nicolas Durrande
Delayed Gradient Averaging: Tolerate the Communication Latency for Federated Studying
Ligeng Zhu, Hongzhou Lin, Yao Lu, Yujun Lin, Music Han
Discrete-Valued Neural Communication
Dianbo Liu, Alex Lamb, Kenji Kawaguchi, Anirudh Goyal, Chen Solar, Michael Curtis Mozer, Yoshua Bengio
Do Imaginative and prescient Transformers See Like Convolutional Neural Networks?
Maithra Raghu, Thomas Unterthiner, Simon Kornblith, Chiyuan Zhang, Alexey Dosovitskiy
Dueling Bandits with Staff Comparisons
Lee Cohen, Ulrike Schmidt-Kraepelin, Yishay Mansour
Finish-to-Finish Multi-Modal Video Temporal Grounding
Yi-Wen Chen, Yi-Hsuan Tsai, Ming-Hsuan Yang
Setting Technology for Zero-Shot Compositional Reinforcement Studying
Izzeddin Gur, Natasha Jaques, Yingjie Miao, Jongwook Choi, Manoj Tiwari, Honglak Lee, Aleksandra Faust
H-NeRF: Neural Radiance Fields for Rendering and Temporal Reconstruction of People in Movement
Hongyi Xu, Thiemo Alldieck, Cristian Sminchisescu
Bettering Calibration By way of the Relationship with Adversarial Robustness
Yao Qin, Xuezhl Wang, Alex Beutel, Ed Chi
Studying Generalized Gumbel-Max Causal Mechanisms
Man Lorberbom, Daniel D. Johnson, Chris J. Maddison, Daniel Tarlow, Tamir Hazan
MICo: Improved Representations by way of Sampling-Primarily based State Similarity for Markov Determination Processes
Pablo Samuel Castro, Tyler Kastner, Prakash Panangaden, Mark Rowland
Close to-Optimum Decrease Bounds For Convex Optimization For All Orders of Smoothness
Ankit Garg, Robin Kothari, Praneeth Netrapalli, Suhail Sherif
Neural Circuit Synthesis from Specification Patterns
Frederik Schmitt, Christopher Hahn, Markus N. Rabe, Bernd Finkbeiner
Non-Native Latent Relation Distillation for Self-Adaptive 3D Human Pose Estimation
Jogendra Nath Kundu, Siddharth Seth, Anirudh Jamkhandi, Pradyumna YM, Varun Jampani, Anirban Chakraborty, R. Venkatesh Babu
Object-Conscious Contrastive Studying for Debiased Scene Illustration
Sangwoo Mo, Hyunwoo Kang, Kihyuk Soh, Chun-Liang Li, Jinwoo Shin
On Density Estimation with Diffusion Fashions
Diederik P. Kingma, Tim Salimans, Ben Poole, Jonathan Ho
On Margin-Primarily based Cluster Restoration with Oracle Queries
Marco Bressan, Nicolo Cesa-Bianchi, Silvio Lattanzi, Andrea Paudice
On Mannequin Calibration for Lengthy-Tailed Object Detection and Occasion Segmentation
Tai-Yu Pan, Cheng Zhang, Yandong Li, Hexiang Hu, Dong Xuan, Soravit Changpinyo, Boqing Gong, Wei-Lun Chao
Parallelizing Thompson Sampling
Amin Karbasi, Vahab Mirrokni, Mohammad Shadravan
Reverse-Complement Equivariant Networks for DNA Sequences
Vincent Mallet, Jean-Philippe Vert
Revisiting ResNets: Improved Coaching and Scaling Methods
Irwan Bello, William Fedus, Xianzhi Du, Ekin Dogus Cubuk, Aravind Srinivas, Tsung-Yi Lin, Jonathon Shlens, Barret Zoph
Revisiting the Calibration of Trendy Neural Networks
Matthias Minderer, Josip Djolonga, Rob Romijnders, Frances Ann Hubis, Xiaohua Zhai, Neil Houlsby, Dustin Tran, Mario Lucic
Scaling Imaginative and prescient with Sparse Combination of Consultants
Carlos Riquelme, Joan Puigcerver, Basil Mustafa, Maxim Neumann, Rodolphe Jenatton, André Susano Pinto, Daniel Keysers, Neil Houlsby
SE(3)-Equivariant Prediction of Molecular Wavefunctions and Digital Densities
Oliver Thorsten Unke, Mihail Bogojeski, Michael Gastegger, Mario Geiger, Tess Smidt, Klaus Robert Muller
Stateful ODE-Nets Utilizing Foundation Operate Expansions
Alejandro Francisco Queiruga, N. Benjamin Erichson, Liam Hodgkinson, Michael W. Mahoney
Statistically and Computationally Environment friendly Linear Meta-Illustration Studying
Kiran Koshy Thekumparampil, Prateek Jain, Praneeth Netrapalli, Sewoong Oh
Streaming Perception Propagation for Neighborhood Detection
Yuchen Wu, Jakab Tardos, Mohammad Hossein Bateni, André Linhares, Filipe Miguel Gonçalves de Almeida, Andrea Montanari, Ashkan Norouzi-Fard
Artificial Design: An Optimization Method to Experimental Design with Artificial Controls
Nick Doudchenko, Khashayar Khosravi, Jean Pouget-Abadie, Sebastien Lahaie, Miles Lubin, Vahab Mirrokni, Jann Spiess, Guido Imbens
The Issue of Passive Studying in Deep Reinforcement Studying
George Ostrovski, Pablo Samuel Castro, Will Dabney
The Pareto Frontier of Mannequin Choice for Normal Contextual Bandits
Teodor Marinov, Julian Zimmert
VATT: Transformers for Multimodal Self-Supervised Studying from Uncooked Video, Audio and Textual content
Hassan Akbari, Liangzhe Yuan, Rui Qian, Wei-Hong Chuang, Shih-Fu Chang, Yin Cui, Boqing Gong
Co-Adaptation of Algorithmic and Implementational Improvements in Inference-Primarily based Deep Reinforcement Studying
Hiroki Furuta, Tadashi Kozuno, Tatsuya Matsushima, Yutaka Matsuo, Shixiang Gu
Conservative Information Sharing for Multi-Activity Offline Reinforcement Studying
Tianhe Yu, Aviral Kumar, Yevgen Chebotar, Karol Hausman, Sergey Levine, Chelsea Finn
Does Information Distillation Actually Work?
Samuel Stanton, Pavel Izmailov, Polina Kirichenko, Alexander A. Alemi, Andrew Gordon Wilson
Exponential Graph is Provably Environment friendly for Decentralized Deep Coaching
Bicheng Ying, Kun Yuan, Yiming Chen, Hanbin Hu, Pan Pan, Wotao Yin
Sooner Matchings by way of Discovered Duals
Michael Dinitz, Sungjin Im, Thomas Lavastida, Benjamin Moseley, Sergei Vassilvitskii
Improved Transformer for Excessive-Decision GANs
Lengthy Zhao, Zizhao Zhang, Ting Chen, Dimitris N. Metaxas, Han Zhang
Close to-Optimum Offline and Streaming Algorithms for Studying Non-Linear Dynamical Methods
Prateek Jain, Suhas S. Kowshik, Dheeraj Mysore Nagaraj, Praneeth Netrapalli
Almost Horizon-Free Offline Reinforcement Studying
Tongzheng Ren, Jialian Li, Bo Dai, Simon S. Du, Sujay Sanghavi
Overparameterization Improves Robustness to Covariate Shift in Excessive Dimensions
Nilesh Tripuraneni, Ben Adlam, Jeffrey Pennington
Pay Consideration to MLPs
Hanxiao Liu, Zihang Dai, David R. So, Quoc V. Le
PLUR: A Unifying, Graph-Primarily based View of Program Studying, Understanding, and Restore
Zimin Chen*, Vincent Josua Hellendoorn*, Pascal Lamblin, Petros Maniatis, Pierre-Antoine Manzagol, Daniel Tarlow, Subhodeep Moitra
Prior-Impartial Dynamic Auctions for a Worth-Maximizing Purchaser
Yuan Deng, Hanrui Zhang
Bear in mind What You Wish to Neglect: Algorithms for Machine Unlearning
Ayush Sekhari, Jayadev Acharya, Gautam Kamath, Ananda Theertha Suresh
Reverse Engineering Discovered Optimizers Reveals Recognized and Novel Mechanisms
Niru Maheswaranathan*, David Sussillo*, Luke Metz, Ruoxi Solar, Jascha Sohl-Dickstein
Revisiting 3D Object Detection From an Selfish Perspective
Boyang Deng, Charles R. Qi, Mahyar Najibi, Thomas Funkhouser, Yin Zhou, Dragomir Anguelov
Sturdy Public sale Design within the Auto-Bidding World
Santiago Balseiro, Yuan Deng, Jieming Mao, Vahab Mirrokni, Music Zuo
Shift-Sturdy GNNs: Overcoming the Limitations of Localized Graph Coaching Information
Qi Zhu, Natalia Ponomareva, Jiawei Han, Bryan Perozzi
Understanding How Encoder-Decoder Architectures Attend
Kyle Aitken, Vinay V. Ramasesh, Yuan Cao, Niru Maheswaranathan
Understanding the Impact of Stochasticity in Coverage Optimization
Jincheng Mei, Bo Dai, Chenjun Xiao, Csaba Szepesvari, Dale Schuurmans
Precisely Fixing Rod Dynamics with Graph Studying
Han Shao, Tassilo Kugelstadt, Torsten Hädrich, Wojtek Palubicki, Jan Bender, Sören Pirk, Dominik L. Michels
GradInit: Studying to Initialize Neural Networks for Steady and Environment friendly Coaching
Chen Zhu, Renkun Ni, Zheng Xu, Kezhi Kong, W. Ronny Huang, Tom Goldstein
Learnability of Linear Thresholds from Label Proportions
Rishi Saket
MLP-Mixer: An All-MLP Structure for Imaginative and prescient
Ilya Tolstikhin, Neil Houlsby, Alexander Kolesnikov, Lucas Beyer, Xiaohua Zhai, Thomas Unterthiner, Jessica Yung, Andreas Steiner, Daniel Keysers, Jakob Uszkoreit, Mario Lucic, Alexey Dosovitskiy
Neural Additive Fashions: Interpretable Machine Studying with Neural Nets
Rishabh Agarwal, Levi Melnick, Nicholas Frosst, Xuezhou Zhang, Ben Lengerich, Wealthy Caruana, Geoffrey Hinton
Neural Manufacturing Methods
Anirudh Goyal, Aniket Didolkar, Nan Rosemary Ke, Charles Blundell, Philippe Beaudoin, Nicolas Heess, Michael Mozer, Yoshua Bengio
Physics-Conscious Downsampling with Deep Studying for Scalable Flood Modeling
Niv Giladi, Zvika Ben-Haim, Sella Nevo, Yossi Matias, Daniel Soudry
Form from Blur: Recovering Textured 3D Form and Movement of Quick Shifting Objects
Denys Rozumnyi, Martin R. Oswald, Vittorio Ferrari, Marc Pollefeys
What Issues for Adversarial Imitation Studying?
Manu Orsini, Anton Raichuk, Léonard Hussenot, Damien Vincent, Robert Dadashi, Sertan Girgin, Matthieu Geist, Olivier Bachem, Olivier Pietquin, Marcin Andrychowicz
A Convergence Evaluation of Gradient Descent on Graph Neural Networks
Pranjal Awasthi, Abhimanyu Das, Sreenivas Gollapudi
A Geometric Evaluation of Neural Collapse with Unconstrained Options
Zhihui Zhu, Tianyu Ding, Jinxin Zhou, Xiao Li, Chong You, Jeremias Sulam, Qing Qu
Agnostic Reinforcement Studying with Low-Rank MDPs and Wealthy Observations
Christoph Dann, Yishay Mansour, Mehryar Mohri, Ayush Sekhari, Karthik Sridharan
Managed Textual content Technology as Steady Optimization with A number of Constraints
Sachin Kumar, Eric Malmi, Aliaksei Severyn, Yulia Tsvetkov
Coupled Gradient Estimators for Discrete Latent Variables
Zhe Dong, Andriy Mnih, George Tucker
Detecting Errors and Estimating Accuracy on Unlabeled Information with Self-Coaching Ensembles
Jiefeng Chen*, Frederick Liu, Besim Avci, Xi Wu, Yingyu Liang, Somesh Jha
Neural Lively Studying with Efficiency Ensures
Zhilei Wang, Pranjal Awasthi, Christoph Dann, Ayush Sekhari, Claudio Gentile
Optimum Sketching for Hint Estimation
Shuli Jiang, Hai Pham, David Woodruff, Qiuyi (Richard) Zhang
Representing Lengthy-Vary Context for Graph Neural Networks with International Consideration
Zhanghao Wu, Paras Jain, Matthew A. Wright, Azalia Mirhoseini, Joseph E. Gonzalez, Ion Stoica
Scaling Up Precise Neural Community Compression by ReLU Stability
Thiago Serra, Xin Yu, Abhinav Kumar, Srikumar Ramalingam
Mushy Calibration Targets for Neural Networks
Archit Karandikar, Nicholas Cain, Dustin Tran, Balaji Lakshminarayanan, Jonathon Shlens, Michael Curtis Mozer, Rebecca Roelofs
Sub-Linear Reminiscence: The best way to Make Performers SLiM
Valerii Likhosherstov, Krzysztof Choromanski, Jared Davis, Xingyou Music, Adrian Weller
A New Theoretical Framework for Quick and Correct On-line Determination-Making
Nicolò Cesa-Bianchi, Tommaso Cesari, Yishay Mansour, Vianney Perchet
Bridging the Hole Between Follow and PAC-Bayes Concept in Few-Shot Meta-Studying
Nan Ding, Xi Chen, Tomer Levinboim, Sebastian Goodman, Radu Soricut
Differentially Non-public Multi-Armed Bandits within the Shuffle Mannequin
Jay Tenenbaum, Haim Kaplan, Yishay Mansour, Uri Stemmer
Environment friendly and Native Parallel Random Walks
Michael Kapralov, Silvio Lattanzi, Navid Nouri, Jakab Tardos
Bettering Anytime Prediction with Parallel Cascaded Networks and a Temporal-Distinction Loss
Michael Louis Iuzzolino, Michael Curtis Mozer, Samy Bengio*
It Has Potential: Gradient-Pushed Denoisers for Convergent Options to Inverse Issues
Regev Cohen, Yochai Blau, Daniel Freedman, Ehud Rivlin
Studying to Mix Per-Instance Options for Neural Program Synthesis
Disha Shrivastava, Hugo Larochelle, Daniel Tarlow
LLC: Correct, Multi-purpose Learnt Low-Dimensional Binary Codes
Aditya Kusupati, Matthew Wallingford, Vivek Ramanujan, Raghav Somani, Jae Sung Park, Krishna Pillutla, Prateek Jain, Sham Kakade, Ali Farhadi
There Is No Turning Again: A Self-Supervised Method for Reversibility-Conscious Reinforcement Studying (see weblog publish)
Nathan Grinsztajn, Johan Ferret, Olivier Pietquin, Philippe Preux, Matthieu Geist
A Close to-Optimum Algorithm for Debiasing Educated Machine Studying Fashions
Ibrahim Alabdulmohsin, Mario Lucic
Adaptive Sampling for Minimax Truthful Classification
Shubhanshu Shekhar, Greg Fields, Mohammad Ghavamzadeh, Tara Javidi
Asynchronous Stochastic Optimization Sturdy to Arbitrary Delays
Alon Cohen, Amit Daniely, Yoel Drori, Tomer Koren, Mariano Schain
Boosting with A number of Sources
Corinna Cortes, Mehryar Mohri, Dmitry Storcheus, Ananda Theertha Suresh
Breaking the Centralized Barrier for Cross-Machine Federated Studying
Sai Praneeth Karimireddy, Martin Jaggi, Satyen Kale, Mehryar Mohri, Sashank J. Reddi, Sebastian U. Sew, Ananda Theertha Sureshi
Canonical Capsules: Self-Supervised Capsules in Canonical Pose
Weiwei Solar, Andrea Tagliasacchi, Boyang Deng, Sara Sabour, Soroosh Yazdani, Geoffrey Hinton, Kwang Moo Yi
Contextual Suggestions and Low-Remorse Slicing-Aircraft Algorithms
Sreenivas Gollapudi, Guru Guruganesh, Kostas Kollias, Pasi Manurangsi, Renato Paes Leme, Jon Schneider
Determination Transformer: Reinforcement Studying by way of Sequence Modeling
Lili Chen, Kevin Lu, Aravind Rajeswaran, Kimin Lee|Aditya Grover, Michael Laskin, Pieter Abbeel, Aravind Srinivas, Igor Mordatch
Deep Studying on a Information Weight loss program: Discovering Essential Examples Early in Coaching
Mansheej Paul, Surya Ganguli, Gintare Karolina Dziugaite
Deep Studying with Label Differential Privateness
Badih Ghazi, Noah Golowich*, Ravi Kumar, Pasin Manurangsi, Chiyuan Zhang
Environment friendly Coaching of Retrieval Fashions Utilizing Destructive Cache
Erik Lindgren, Sashank J. Reddi, Ruiqi Guo, Sanjiv Kumar
Exploring Cross-Video and Cross-Modality Indicators for Weakly-Supervised Audio-Visible Video Parsing
Yan-Bo Lin, Hung-Yu Tseng, Hsin-Ying Lee, Yen-Yu Lin, Ming-Hsuan Yang
Federated Reconstruction: Partially Native Federated Studying
Karan Singhal, Hakim Sidahmed, Zachary Garrett, Shanshan Wu, Keith Rush, Sushant Prakash
Framing RNN as a Kernel Methodology: A Neural ODE Method
Adeline Fermanian, Pierre Marion, Jean-Philippe Vert, Gérard Biau
Studying Semantic Representations to Confirm {Hardware} Designs
Shobha Vasudevan, Wenjie Jiang, David Bieber, Rishabh Singh, Hamid Shojaei, C. Richard Ho, Charles Sutton
Studying with Person-Stage Privateness
Daniel Asher Nathan Levy*, Ziteng Solar*, Kareem Amin, Satyen Kale, Alex Kulesza, Mehryar Mohri, Ananda Theertha Suresh
Logarithmic Remorse from Sublinear Hints
Aditya Bhaskara, Ashok Cutkosky, Ravi Kumar, Manish Purohit
Margin-Impartial On-line Multiclass Studying by way of Convex Geometry
Guru Guruganesh, Allen Liu, Jon Schneider, Joshua Ruizhi Wang
Multiclass Boosting and the Price of Weak Studying
Nataly Brukhim, Elad Hazan, Shay Moran, Indraneel Mukherjee, Robert E. Schapire
Neural-PIL: Neural Pre-integrated Lighting for Reflectance Decomposition
Mark Boss, Varun Jampani, Raphael Braun, Ce Liu*, Jonathan T. Barron, Hendrik Lensch
By no means Go Full Batch (in Stochastic Convex Optimization)
Idan Amir, Yair Carmon, Tomer Koren, Roi Livni
On Massive-Cohort Coaching for Federated Studying
Zachary Charles, Zachary Garrett, Zhouyuan Huo, Sergei Shmulyian, Virginia Smith
On the Pattern Complexity of Privately Studying Axis-Aligned Rectangles
Menachem Sadigurschi, Uri Stemmer
On-line Management of Unknown Time-Various Dynamical Methods
Edgar Minasyan, Paula Gradu, Max Simchowitz, Elad Hazan
On-line Knapsack with Frequency Predictions
Sungjin Im, Ravi Kumar,Mahshid Montazer Qaem, Manish Purohit
Optimum Charges for Random Order On-line Optimization
Uri Sherman, Tomer Koren, Yishay Mansour
Oracle-Environment friendly Remorse Minimization in Factored MDPs with Unknown Construction
Aviv Rosenberg, Yishay Mansour
Sensible Massive-Scale Linear Programming Utilizing Primal-Twin Hybrid Gradient
David Applegate, Mateo Díaz*, Oliver Hinder, Haihao Lu*, Miles Lubin, Brendan O’Donoghue, Warren Schudy
Non-public and Non-Non-public Uniformity Testing for Rating Information
Robert Istvan Busa-Fekete, Dimitris Fotakis, Manolis Zampetakis
Privately Studying Subspaces
Vikrant Singhal, Thomas Steinke
Provable Illustration Studying for Imitation with Contrastive Fourier Options
Ofir Nachum, Mengjiao Yang
Secure Reinforcement Studying with Pure Language Constraints
Tsung-Yen Yang, Michael Hu, Yinlam Chow, Peter J. Ramadge, Karthik Narasimhan
Looking for Environment friendly Transformers for Language Modeling
David R. So, Wojciech Mańke, Hanxiao Liu, Zihang Dai, Noam Shazeer, Quoc V. Le
SLOE: A Sooner Methodology for Statistical Inference in Excessive-Dimensional Logistic Regression
Steve Yadlowsky, Taedong Yun, Cory McLean, Alexander D’Amour
Streaming Linear System Identification with Reverse Expertise Replay
Prateek Jain, Suhas S. Kowshik, Dheeraj Mysore Nagaraj, Praneeth Netrapalli
The Skellam Mechanism for Differentially Non-public Federated Studying
Naman Agarwal, Peter Kairouz, Ziyu Liu*
TokenLearner: Adaptive House-Time Tokenization for Movies
Michael S. Ryoo, AJ Piergiovanni, Anurag Arnab, Mostafa Dehghani, Anelia Angelova
In direction of Greatest-of-All-Worlds On-line Studying with Suggestions Graphs
Liad Erez, Tomer Koren
Coaching Over-Parameterized Fashions with Non-decomposable Targets
Harikrishna Narasimhan, Aditya Krishna Menon
Twice Regularized MDPs and the Equivalence Between Robustness and Regularization
Esther Derman, Matthieu Geist, Shie Mannor
Unsupervised Studying of Compositional Vitality Ideas
Yilun Du, Shuang Li, Yash Sharma, Joshua B. Tenenbaum, Igor Mordatch
Person-Stage Differentially Non-public Studying by way of Correlated Sampling
Badih Ghazi, Ravi Kumar, Pasin Manurangsi
ViSER: Video-Particular Floor Embeddings for Articulated 3D Form Reconstruction
Gengshan Yang, Deqing Solar, Varun Jampani, Daniel Vlasic, Forrester Cole, Ce Liu*, Deva Ramanan
A Minimalist Method to Offline Reinforcement Studying
Scott Fujimoto, Shixiang Gu
A Unified View of cGANs With and With out Classifiers
Si-An Chen, Chun-Liang Li, Hsuan-Tien Lin
CoAtNet: Marrying Convolution and Consideration for All Information Sizes (see weblog publish)
Zihang Dai, Hanxiao Liu, Quoc V. Le, Mingxing Tan
Combiner: Full Consideration Transformer with Sparse Computation Price
Hongyu Ren*, Hanjun Dai, Zihang Dai, Mengjiao Yang, Jure Leskovec, Dale Schuurmans, Bo Dai
Contrastively Disentangled Sequential Variational Autoencoder
Junwen Bai, Weiran Wang, Carla P. Gomes
Controlling Neural Networks with Rule Representations
Sungyong Website positioning, Sercan O. Arik, Jinsung Yoon, Xiang Zhang, Kihyuk Sohn, Tomas Pfister
Dataset Distillation with Infinitely Large Convolutional Networks
Timothy Nguyen*, Roman Novak, Lechao Xiao, Jaehoon Lee
Deep Synoptic Monte-Carlo Planning in Reconnaissance Blind Chess
Gregory Clark
Differentially Non-public Studying with Adaptive Clipping
Galen Andrew, Om Thakkar, Swaroop Ramaswamy, Hugh Brendan McMahan
Differentially Non-public Mannequin Personalization
Prateek Jain, Keith Rush, Adam Smith, Shuang Music, Abhradeep Thakurta
Environment friendly Algorithms for Studying Depth-2 Neural Networks with Normal ReLU Activations
Pranjal Awasthi, Alex Tang, Aravindan Vijayaraghavan
Effectively Figuring out Activity Groupings for Multi-Activity Studying
Christopher Fifty, Ehsan Amid, Zhe Zhao, Tianhe Yu, Rohan Anil, Chelsea Finn
Generalized Form Metrics on Neural Representations
Alex H. Williams, Erin Kunz, Simon Kornblith, Scott Linderman
Excessive-Chance Bounds for Non-Convex Stochastic Optimization with Heavy Tails
Ashok Cutkosky, Harsh Mehta
Identification Testing for Mallows Mannequin
Róbert Busa-Fekete, Dimitris Fotakis, Balázs Szörényi, Manolis Zampetakis
Learnable Fourier Options for Multi-dimensional Spatial Positional Encoding
Yang Li, Si Si, Gang Li, Cho-Jui Hsieh, Samy Bengio*
Studying to Choose Exogenous Occasions for Marked Temporal Level Course of
Ping Zhang, Rishabh Okay. Iyer, Ashish V. Tendulkar, Gaurav Aggarwal, Abir De
Meta-learning to Enhance Pre-training
Aniruddh Raghu, Jonathan Peter Lorraine, Simon Kornblith, Matthew B.A. McDermott, David Duvenaud
Pointwise Bounds for Distribution Estimation Below Communication Constraints
Wei-Ning Chen, Peter Kairouz, Ayfer Özgür
REMIPS: Bodily Constant 3D Reconstruction of A number of Interacting Individuals Below Weak Supervision
Mihai Fieraru, Mihai Zanfir, Teodor Alexandru Szente, Eduard Gabriel Bazavan, Vlad Olaru, Cristian Sminchisescu
Changing Rewards with Examples: Instance-Primarily based Coverage Search by way of Recursive Classification
Benjamin Eysenbach, Sergey Levine, Ruslan Salakhutdinov
Revealing and Defending Labels in Distributed Coaching
Trung Dang, Om Thakkar, Swaroop Ramaswamy, Rajiv Mathews, Peter Chin, Françoise Beaufays
Sturdy Predictable Management
Benjamin Eysenbach, Ruslan Salakhutdinov, Sergey Levine
Sturdy Visible Reasoning by way of Language Guided Neural Module Networks
Arjun Reddy Akula, Varun Jampani, Soravit Changpinyo, Music-Chun Zhu
In direction of Understanding Retrosynthesis by Vitality-Primarily based Fashions
Ruoxi Solar, Hanjun Dai, Li Li, Steven Kearnes, Bo Dai
Exploring the Limits of Out-of-Distribution Detection
Stanislav Fort, Jie Ren, Balaji Lakshminarayanan
Minimax Remorse for Stochastic Shortest Path
Alon Cohen, Yonathan Efroni, Yishay Mansour, Aviv Rosenberg
No Regrets for Studying the Prior in Bandits
Soumya Basu, Branislav Kveton, Manzil Zaheer, Csaba Szepesvari
Structured Denoising Diffusion Fashions in Discrete State-Areas
Jacob Austin, Daniel D. Johnsonv, Jonathan Ho, Daniel Tarlow, Rianne van den Berg
The Sensory Neuron as a Transformer: Permutation-Invariant Neural Networks for Reinforcement Studying (see weblog publish)
Yujin Tang, David Ha
On the Existence of The Adversarial Bayes Classifier
Pranjal Awasthi, Natalie Frank, Mehyrar Mohri
Past Worth-Operate Gaps: Improved Occasion-Dependent Remorse Bounds for Episodic Reinforcement Studying
Christopher Dann, Teodor Vanislavov Marinov, Mehryar Mohri, Julian Zimmert
A Provably Environment friendly Mannequin-Free Posterior Sampling Methodology for Episodic Reinforcement Studying
Christopher Dann, Mehryar Mohri, Tong Zhang, Julian Zimmert
Datasets & Benchmarks Accepted Papers
Decreased, Reused and Recycled: The Lifetime of a Dataset in Machine Studying Analysis
Bernard Koch, Emily Denton, Alex Hanna, Jacob G. Foster
Datasets & Benchmarks Greatest Paper
Establishing a Visible Dataset to Research the Results of Spatial Apartheid in South Africa
Raesetje Sefala, Timnit Gebru, Luzango Mfupe, Nyalleng Moorosi
AI and the Every thing within the Complete Large World Benchmark
Inioluwa Deborah Raji, Emily M. Bender, Amandalynne Paullada, Emily Denton, Alex Hannah
A Unified Few-Shot Classification Benchmark to Evaluate Switch and Meta Studying Approaches
Vincent Dumoulin, Neil Houlsby, Utku Evci, Xiaohua Zhai, Ross Goroshin, Sylvain Gelly, Hugo Larochelle
The Neural MMO Platform for Massively Multi-agent Analysis
Joseph Suarez, Yilun Du, Clare Zhu, Igor Mordatch, Phillip Isola
Systematic Analysis of Causal Discovery in Visible Mannequin-Primarily based Reinforcement Studying
Nan Rosemary Ke, Aniket Didolkar, Sarthak Mittal, Anirudh Goyal, Guillaume Lajole, Stefan Bauer, Danilo Rezende, Yoshua Bengio, Michael Mozer, Christopher Pal
STEP: Segmenting and Monitoring Each Pixel
Mark Weber, Jun Xie, Maxwell Collins, Yukun Zhu, Paul Voigtlaender, Hartwig Adam, Bradley Inexperienced, Andreas Geiger, Bastian Leibe, Daneil Cremers, Aljosa Osep, Laura Leal-Taixe, Liang-Chieh Chen
Artsheets for Artwork Datasets
Ramya Srinivisan, Emily Denton, Jordan Famularo, Negar Rostamzadeh, Fernando Diaz, Beth Coleman
SynthBio: A Case in Human–AI Collaborative Curation of Textual content Datasets
Ann Yuan, Daphne Ippolito, Vitaly Niolaev, Chris Callison-Burch, Andy Coenen, Sebastian Gehrmann
Benchmarking Bayesian Deep Studying on Diabetic Retinopathy Detection Duties
Neil Band, Tim G. J. Rudner, Qixuan Feng, Angelos Filos, Zachary Nado, Michael W. Dusenberry, Ghassen Jerfel, Dustin Tran, Yarin Gal
Brax – A Differentiable Physics Engine for Massive Scale Inflexible Physique Simulation (see weblog publish)
C. Daniel Freeman, Erik Frey, Anton Raichuk, Sertan Girgin, Igor Mordatch, Olivier Bachem
MLPerf Tiny Benchmark
Colby Banbury, Vijay Janapa Reddi, Peter Torelli, Jeremy Holleman, Nat Jeffries, Csaba Kiraly, Pietro Montino, David Kanter, Sebastian Ahmed, Danilo Pau, Urmish Thakker, Antonio Torrini, Peter Warden, Jay Cordaro, Giuseppe Di Guglielmo, Javier Duarte, Stephen Gibellini, Videet Parekh, Honson Tran, Nhan Tran, Niu Wenxu, Xu Xuesong
Automated Building of Analysis Suites for Pure Language Technology Datasets
Simon Mille, Kaustubh D. Dhole, Saad Mahamood, Laura Perez-Beltrachini, Varun Gangal, Mihir Kale, Emiel van Miltenburg, Sebastian Gehrmann
An Empirical Investigation of Illustration Studying for Imitation
Xin Chen, Sam Toyer, Cody Wild, Scott Emmons, Ian Fischer, Kuang-Huei Lee, Neel Alex, Steven Wang, Ping Luo, Stuart Russell, Pieter Abbeel, Rohin Shah
Multilingual Spoken Phrases Corpus
Mark Mazumder, Sharad Chitlangia, Colby Banbury, Yiping Kang, Juan Manuel Ciro, Keith Achorn, Daniel Galvez, Mark Sabini, Peter Mattson, David Kanter, Greg Diamos, Pete Warden, Josh Meyer, Vijay Janapa Reddi
Workshops
4th Robotic Studying Workshop: Self-Supervised and Lifelong Studying
Sponsor: Google
Organizers embody Alex Bewley, Vincent Vanhoucke
Differentiable Programming Workshop
Sponsor: Google
Machine Studying for Creativity and Design
Sponsor: Google
Organizers embody: Daphne Ippolito, David Ha
LatinX in AI (LXAI) Analysis @ NeurIPS 2021
Sponsor: Google
Sponsorship Stage: Platinum
Workshop Chairs embody: Andres Munoz Medina
Mentorship Roundtables embody: Jonathan Huang, Pablo Samuel Castro
Algorithmic Equity By way of the Lens of Causality and Robustness
Organizers embody: Jessica Schrouff, Awa Dieng
ImageNet: Previous, Current, and Future
Organizers embody: Lucas Beyer, Xiaohua Zhai
Audio system embody: Emily Denton, Vittorio Ferrari, Alex Hanna, Alex Kolesnikov, Rebecca Roelofs
Optimum Transport and Machine Studying
Organizers embody: Marco Cuturi
Secure and Sturdy Management of Unsure Methods
Audio system embody: Aleksandra Faust
CtrlGen: Controllable Generative Modeling in Language and Imaginative and prescient
Audio system embody: Sebastian Gehrmann
Deep Reinforcement Studying
Organizers embody: Chelsea Finn
Audio system embody: Karol Hausam, Dale Schuurmans
Distribution Shifts: Connecting Strategies and Functions (DistShift)
Audio system embody: Chelsea Finn
ML For Methods
Organizers embody: Anna Goldie, Martin Maas, Azade Nazi, Azalia Mihoseini, Milad Hashemi, Kevin Swersky
Studying in Presence of Strategic Habits
Organizers embody: Yishay Mansour
Bayesian Deep Studying
Organizers embody: Zoubin Ghahramani, Kevin Murphy
Advances in Programming Languages and Neurosymbolic Methods (AIPLANS)
Organizers embody: Disha Shrivastava, Vaibhav Tulsyan, Danny Tarlow
Ecological Concept of Reinforcement Studying: How Does Activity Design Affect Agent Studying?
Organizers embody: Shixiang Shane Gu, Pablo Samuel Castro, Marc G. Bellemare
The Symbiosis of Deep Studying and Differential Equations
Organizers embody: Lily Hu
Out-of-Distribution Generalization and Adaptation in Pure and Synthetic Intelligence
Audio system embody: Chelsea Finn
Cooperative AI
Organizers embody: Natasha Jaques
Offline Reinforcement Studying
Organizers embody: Rishabh Agarwal, George Tucker
Audio system embody: Minmin Chen
2nd Workshop on Self-Supervised Studying: Concept and Follow
Organizers embody: Kristina Toutanova
Information Centric AI
Organizers embody: Lora Aroyo
Math AI for Schooling (MATHAI4ED): Bridging the Hole Between Analysis and Good Schooling
Organizers embody: Yuhai (Tony) Wu
Tutorials
Past Equity in Machine Studying
Organizers embody: Emily Denton
Competitions
Evaluating Approximate Inference in Bayesian Deep Studying
Organizers embody: Matthew D. Hoffman, Sharad Vikram
HEAR 2021 NeurIPS Problem Holistic Analysis of Audio Representations
Organizers embody: Jesse Engel
Machine Studying for Combinatorial Optimization
Organizers embody: Pawel Lichocki, Miles Lubin
*Work finished whereas at Google. ↩
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