Filter by Keyword:

118 Results

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 Neural Approximate Sufficient Statistics for Implicit Models
Yanzhi Chen, Dinghuai Zhang, Michael U Gutmann, Aaron Courville, Zhanxing Zhu
Poster
Mon 1:00 Exploring Balanced Feature Spaces for Representation Learning
Bingyi Kang, Yu Li, Sain Xie, Zehuan Yuan, Jiashi Feng
Poster
Mon 1:00 On Learning Universal Representations Across Languages
Xiangpeng Wei, Rongxiang Weng, Yue Hu, Luxi Xing, Heng Yu, Weihua Luo
Poster
Mon 1:00 Towards Impartial Multi-task Learning
Liyang Liu, Yi Li, Zhanghui Kuang, Jing-Hao Xue, Yimin Chen, Wenming Yang, Qingmin Liao, Wei Zhang
Poster
Mon 1:00 The Unreasonable Effectiveness of Patches in Deep Convolutional Kernels Methods
Louis THIRY, Michael Arbel, Eugene Belilovsky, Edouard Oyallon
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, Taliah Muhammad, Erick M Cobos, Andreas Tolias, Alexander S Ecker, Fabian Sinz
Spotlight
Mon 4:40 How Benign is Benign Overfitting ?
Amartya Sanyal, Puneet Dokania, Varun Kanade, Philip Torr
Poster
Mon 9:00 Learning Structural Edits via Incremental Tree Transformations
Ziyu Yao, Frank F Xu, Pengcheng Yin, Huan Sun, Graham Neubig
Poster
Mon 9:00 InfoBERT: Improving Robustness of Language Models from An Information Theoretic Perspective
Boxin Wang, Shuohang Wang, Yu Cheng, Zhe Gan, Ruoxi Jia, Bo Li, Jingjing Liu
Poster
Mon 9:00 Parameter Efficient Multimodal Transformers for Video Representation Learning
Sangho Lee, Youngjae Yu, Gunhee Kim, Thomas Breuel, Jan Kautz, Yale Song
Poster
Mon 9:00 Learning Hyperbolic Representations of Topological Features
Panagiotis Kyriakis, Iordanis Fostiropoulos, Paul Bogdan
Poster
Mon 9:00 Gradient Projection Memory for Continual Learning
Gobinda Saha, Isha Garg, Kaushik Roy
Poster
Mon 9:00 What Can You Learn From Your Muscles? Learning Visual Representation from Human Interactions
Kiana Ehsani, Daniel Gordon, Thomas H Nguyen, Roozbeh Mottaghi, Ali Farhadi
Poster
Mon 9:00 Intrinsic-Extrinsic Convolution and Pooling for Learning on 3D Protein Structures
Pedro Hermosilla Casajus, Marco Schäfer, Matej Lang, Gloria Fackelmann, Pere-Pau Vázquez, Barbora Kozlikova, Michael Krone, Tobias Ritschel, Timo Ropinski
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 Learning Invariant Representations for Reinforcement Learning without Reconstruction
Amy Zhang, Rowan T McAllister, Roberto Calandra, Yarin Gal, Sergey Levine
Poster
Mon 9:00 Seq2Tens: An Efficient Representation of Sequences by Low-Rank Tensor Projections
Csaba Toth, Patric Bonnier, Harald Oberhauser
Poster
Mon 9:00 What Should Not Be Contrastive in Contrastive Learning
Tete Xiao, Xiaolong Wang, Alexei Efros, trevor darrell
Poster
Mon 9:00 The Risks of Invariant Risk Minimization
Elan Rosenfeld, Pradeep K Ravikumar, Andrej Risteski
Poster
Mon 9:00 Representation learning for improved interpretability and classification accuracy of clinical factors from EEG
Garrett Honke, Irina Higgins, Nina Thigpen, Vladimir Miskovic, Katie Link, Sunny Duan, Pramod Gupta, Julia Klawohn, Greg Hajcak
Poster
Mon 9:00 Training GANs with Stronger Augmentations via Contrastive Discriminator
Jongheon Jeong, Jinwoo Shin
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
Oral
Mon 11:15 Gradient Projection Memory for Continual Learning
Gobinda Saha, Isha Garg, Kaushik Roy
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 MixKD: Towards Efficient Distillation of Large-scale Language Models
Kevin Liang, Weituo Hao, Dinghan Shen, Yufan Zhou, Weizhu Chen, Changyou Chen, Lawrence Carin
Poster
Mon 17:00 MoPro: Webly Supervised Learning with Momentum Prototypes
Junnan Li, Caiming Xiong, Steven Hoi
Poster
Mon 17:00 DeLighT: Deep and Light-weight Transformer
Sachin Mehta, Marjan Ghazvininejad, Srini Iyer, Luke Zettlemoyer, Hannaneh Hajishirzi
Poster
Mon 17:00 Representation Learning for Sequence Data with Deep Autoencoding Predictive Components
Junwen Bai, Weiran Wang, Yingbo Zhou, Caiming Xiong
Poster
Mon 17:00 On the geometry of generalization and memorization in deep neural networks
Cory Stephenson, Suchismita Padhy, Abhinav Ganesh, Yue Hui, Hanlin Tang, SueYeon Chung
Poster
Mon 17:00 Online Adversarial Purification based on Self-supervised Learning
Changhao Shi, Chester Holtz, Gal Mishne
Poster
Mon 17:00 Zero-shot Synthesis with Group-Supervised Learning
Yunhao Ge, Sami Abu-El-Haija, Gan Xin, Laurent Itti
Poster
Tue 1:00 Accurate Learning of Graph Representations with Graph Multiset Pooling
Jinheon Baek, Minki Kang, Sung Ju Hwang
Poster
Tue 1:00 PDE-Driven Spatiotemporal Disentanglement
Jérémie DONA, Jean-Yves Franceschi, sylvain lamprier, patrick gallinari
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, Taliah Muhammad, Erick M Cobos, Andreas Tolias, Alexander S Ecker, Fabian Sinz
Poster
Tue 1:00 Capturing Label Characteristics in VAEs
Tom W Joy, Sebastian Schmon, Philip Torr, Siddharth N, Tom Rainforth
Poster
Tue 1:00 Prototypical Contrastive Learning of Unsupervised Representations
Junnan Li, Pan Zhou, Caiming Xiong, Steven Hoi
Poster
Tue 1:00 Learning Subgoal Representations with Slow Dynamics
Siyuan Li, Lulu Zheng, Jianhao Wang, Chongjie Zhang
Poster
Tue 1:00 Improving Transformation Invariance in Contrastive Representation Learning
Adam Foster, Rattana Pukdee, Tom Rainforth
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
Poster
Tue 9:00 How Benign is Benign Overfitting ?
Amartya Sanyal, Puneet Dokania, Varun Kanade, Philip Torr
Poster
Tue 9:00 Representation Learning via Invariant Causal Mechanisms
Jovana Mitrovic, Brian McWilliams, Jacob C Walker, Lars Buesing, Charles Blundell
Poster
Tue 9:00 Unsupervised Representation Learning for Time Series with Temporal Neighborhood Coding
Sana Tonekaboni, Danny Eytan, Anna Goldenberg
Poster
Tue 9:00 Anatomy of Catastrophic Forgetting: Hidden Representations and Task Semantics
Vinay Ramasesh, Ethan Dyer, Maithra Raghu
Poster
Tue 9:00 Support-set bottlenecks for video-text representation learning
Mandela Patrick, Po-Yao Huang, Yuki Asano, Florian Metze, Alexander G Hauptmann, Joao F. Henriques, Andrea Vedaldi
Poster
Tue 9:00 Learning Parametrised Graph Shift Operators
George Dasoulas, Johannes Lutzeyer, Michalis Vazirgiannis
Poster
Tue 9:00 Interpreting Knowledge Graph Relation Representation from Word Embeddings
Carl Allen, Ivana Balazevic, Timothy Hospedales
Poster
Tue 9:00 Unsupervised Object Keypoint Learning using Local Spatial Predictability
Anand Gopalakrishnan, Sjoerd van Steenkiste, Jürgen Schmidhuber
Poster
Tue 9:00 SSD: A Unified Framework for Self-Supervised Outlier Detection
Vikash Sehwag, Mung Chiang, Prateek Mittal
Poster
Tue 9:00 Data-Efficient Reinforcement Learning with Self-Predictive Representations
Max Schwarzer, Ankesh Anand, Rishab Goel, R Devon Hjelm, Aaron Courville, Philip Bachman
Poster
Tue 9:00 Decoupling Global and Local Representations via Invertible Generative Flows
Xuezhe Ma, Xiang Kong, Shanghang Zhang, Eduard H Hovy
Oral
Tue 11:15 Learning Generalizable Visual Representations via Interactive Gameplay
Luca Weihs, Aniruddha Kembhavi, Kiana Ehsani, Sarah M Pratt, Winson Han, Alvaro Herrasti, Eric Kolve, Dustin Schwenk, Roozbeh Mottaghi, Ali Farhadi
Poster
Tue 17:00 Usable Information and Evolution of Optimal Representations During Training
Michael Kleinman, Alessandro Achille, Daksh Idnani, Jonathan Kao
Poster
Tue 17:00 Universal Weakly Supervised Segmentation by Pixel-to-Segment Contrastive Learning
Tsung-Wei Ke, Jyh-Jing Hwang, Stella Yu
Poster
Tue 17:00 Viewmaker Networks: Learning Views for Unsupervised Representation Learning
Alex Tamkin, Mike Wu, Noah Goodman
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
Wed 1:00 Negative Data Augmentation
Abhishek Sinha, Kumar Ayush, Jiaming Song, Burak Uzkent, Hongxia Jin, Stefano Ermon
Poster
Wed 1:00 Disentangled Recurrent Wasserstein Autoencoder
Jun Han, Martin Min, Ligong Han, Li Erran Li, Xuan Zhang
Poster
Wed 1:00 Return-Based Contrastive Representation Learning for Reinforcement Learning
Guoqing Liu, Chuheng Zhang, Li Zhao, Tao Qin, Jinhua Zhu, Li Jian, Nenghai Yu, Tie-Yan Liu
Poster
Wed 1:00 Relating by Contrasting: A Data-efficient Framework for Multimodal Generative Models
Yuge Shi, Brooks Paige, Philip Torr, Siddharth N
Poster
Wed 1:00 Active Contrastive Learning of Audio-Visual Video Representations
Shuang Ma, Zhaoyang Zeng, Daniel McDuff, Yale Song
Poster
Wed 1:00 Knowledge distillation via softmax regression representation learning
Jing Yang, Brais Martinez, Adrian Bulat, Georgios Tzimiropoulos
Poster
Wed 1:00 Learning from Demonstration with Weakly Supervised Disentanglement
Yordan Hristov, Subramanian Ramamoorthy
Spotlight
Wed 3:45 Support-set bottlenecks for video-text representation learning
Mandela Patrick, Po-Yao Huang, Yuki Asano, Florian Metze, Alexander G Hauptmann, Joao F. Henriques, Andrea Vedaldi
Spotlight
Wed 5:35 Neural Approximate Sufficient Statistics for Implicit Models
Yanzhi Chen, Dinghuai Zhang, Michael U Gutmann, Aaron Courville, Zhanxing Zhu
Poster
Wed 9:00 For self-supervised learning, Rationality implies generalization, provably
Yamini Bansal, Gal Kaplun, Boaz Barak
Poster
Wed 9:00 Learning Generalizable Visual Representations via Interactive Gameplay
Luca Weihs, Aniruddha Kembhavi, Kiana Ehsani, Sarah M Pratt, Winson Han, Alvaro Herrasti, Eric Kolve, Dustin Schwenk, Roozbeh Mottaghi, Ali Farhadi
Poster
Wed 9:00 Learning to Represent Action Values as a Hypergraph on the Action Vertices
Arash Tavakoli, Mehdi Fatemi, Petar Kormushev
Poster
Wed 9:00 Graph Traversal with Tensor Functionals: A Meta-Algorithm for Scalable Learning
Elan Markowitz, Keshav Balasubramanian, Mehrnoosh Mirtaheri, Sami Abu-El-Haija, Bryan Perozzi, Greg Ver Steeg, Aram Galstyan
Poster
Wed 9:00 SEED: Self-supervised Distillation For Visual Representation
Zhiyuan Fang, Jianfeng Wang, Lijuan Wang, Lei Zhang, 'YZ' Yezhou Yang, Zicheng Liu
Poster
Wed 9:00 Boost then Convolve: Gradient Boosting Meets Graph Neural Networks
Sergei Ivanov, Liudmila Prokhorenkova
Poster
Wed 9:00 Property Controllable Variational Autoencoder via Invertible Mutual Dependence
Xiaojie Guo, Yuanqi Du, Liang Zhao
Oral
Wed 11:30 Learning Invariant Representations for Reinforcement Learning without Reconstruction
Amy Zhang, Rowan T McAllister, Roberto Calandra, Yarin Gal, Sergey Levine
Spotlight
Wed 13:18 Unsupervised Object Keypoint Learning using Local Spatial Predictability
Anand Gopalakrishnan, Sjoerd van Steenkiste, Jürgen Schmidhuber
Expo Talk Panel
Wed 14:00 Live Panel - Academics@ Presents: Representation Learning at Amazon
Zahra Matson
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 Beyond Fully-Connected Layers with Quaternions: Parameterization of Hypercomplex Multiplications with $1/n$ Parameters
Aston Zhang, Yi Tay, Shuai Zhang, Alvin Chan, Anh Tuan Luu, Siu Hui, Jie Fu
Poster
Wed 17:00 Control-Aware Representations for Model-based Reinforcement Learning
Brandon Cui, Yinlam Chow, Mohammad Ghavamzadeh
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 Beyond Categorical Label Representations for Image Classification
Boyuan Chen, Yu Li, Sunand Raghupathi, Hod Lipson
Poster
Wed 17:00 Explainable Subgraph Reasoning for Forecasting on Temporal Knowledge Graphs
Zhen Han, Peng Chen, Yunpu Ma, Volker Tresp
Poster
Wed 17:00 BERTology Meets Biology: Interpreting Attention in Protein Language Models
Jesse Vig, Ali Madani, Lav R Varshney, Caiming Xiong, Richard Socher, Nazneen Rajani
Wed 20:00 ML and Language (#1)
Spotlight
Thu 0:45 Beyond Fully-Connected Layers with Quaternions: Parameterization of Hypercomplex Multiplications with $1/n$ Parameters
Aston Zhang, Yi Tay, Shuai Zhang, Alvin Chan, Anh Tuan Luu, Siu Hui, Jie Fu
Poster
Thu 1:00 Impact of Representation Learning in Linear Bandits
Jiaqi Yang, Wei Hu, Jason Lee, Simon Du
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 Inductive Representation Learning in Temporal Networks via Causal Anonymous Walks
Yanbang Wang, Yen-Yu Chang, Yunyu Liu, Jure Leskovec, Pan Li
Poster
Thu 1:00 Learnable Embedding sizes for Recommender Systems
Siyi Liu, Chen Gao, Yihong Chen, Depeng Jin, Yong Li
Poster
Thu 9:00 Improving Zero-Shot Voice Style Transfer via Disentangled Representation Learning
Siyang Yuan, Pengyu Cheng, Ruiyi Zhang, Weituo Hao, Zhe Gan, Lawrence Carin
Poster
Thu 9:00 Integrating Categorical Semantics into Unsupervised Domain Translation
Samuel Lavoie, Faruk Ahmed, Aaron Courville
Poster
Thu 9:00 A Mathematical Exploration of Why Language Models Help Solve Downstream Tasks
Nikunj Umesh Saunshi, Sadhika Malladi, Sanjeev Arora
Poster
Thu 9:00 Contrastive Behavioral Similarity Embeddings for Generalization in Reinforcement Learning
Rishabh Agarwal, Marlos C. Machado, Pablo Samuel Castro, Marc G Bellemare
Poster
Thu 9:00 Contrastive Learning with Hard Negative Samples
Joshua Robinson, Ching-Yao Chuang, Suvrit Sra, Stefanie Jegelka
Poster
Thu 9:00 Directed Acyclic Graph Neural Networks
Veronika Thost, Jie Chen
Spotlight
Thu 12:20 Contrastive Behavioral Similarity Embeddings for Generalization in Reinforcement Learning
Rishabh Agarwal, Marlos C. Machado, Pablo Samuel Castro, Marc G Bellemare
Spotlight
Thu 12:40 Data-Efficient Reinforcement Learning with Self-Predictive Representations
Max Schwarzer, Ankesh Anand, Rishab Goel, R Devon Hjelm, Aaron Courville, Philip Bachman
Spotlight
Thu 13:50 Disentangled Recurrent Wasserstein Autoencoder
Jun Han, Martin Min, Ligong Han, Li Erran Li, Xuan Zhang
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 Multi-timescale Representation Learning in LSTM Language Models
Shivangi Mahto, Vy Vo, Javier Turek, Alexander Huth
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 Prototypical Representation Learning for Relation Extraction
Ning Ding, Xiaobin Wang, Yao Fu, Guangwei Xu, Rui Wang, Pengjun Xie, Ying Shen, Fei Huang, Hai-Tao Zheng, Rui Zhang
Poster
Thu 17:00 Clustering-friendly Representation Learning via Instance Discrimination and Feature Decorrelation
Yaling Tao, Kentaro Takagi, Kouta Nakata
Poster
Thu 17:00 Self-supervised Representation Learning with Relative Predictive Coding
Yao-Hung Hubert Tsai, Martin Q Ma, Muqiao Yang, Han Zhao, Louis-Philippe Morency, Ruslan Salakhutdinov
Poster
Thu 17:00 Self-supervised Learning from a Multi-view Perspective
Yao-Hung Hubert Tsai, Yue Wu, Ruslan Salakhutdinov, Louis-Philippe Morency
Poster
Thu 17:00 CO2: Consistent Contrast for Unsupervised Visual Representation Learning
Chen Wei, Huiyu Wang, Wei Shen, Alan Yuille
Poster
Thu 17:00 Few-Shot Learning via Learning the Representation, Provably
Simon Du, Wei Hu, Sham M Kakade, Jason Lee, Qi Lei
Workshop
Fri 5:00 Geometric and Topological Representation Learning
Guy Wolf, Xiuyuan Cheng, Smita Krishnaswamy, Jure Leskovec, Bastian Rieck, Soledad Villar
Workshop
Fri 5:00 S2D-OLAD: From shallow to deep, overcoming limited and adverse data
Colin Bellinger, Roberto Corizzo, Vincent Dumoulin, Nathalie Japkowicz
Workshop
Fri 6:00 Workshop on Neural Architecture Search
Arber Zela, Aaron Klein, Frank Hutter, Liam Li, Jan Hendrik Metzen, Jovita Lukasik
Workshop
Fri 6:10 Voice2Series: Reprogramming Acoustic Models for Time Series Classification
Huck Yang
Workshop
Fri 6:18 Adversarial Data Augmentation Improves Unsupervised Machine Learning
Chia-Yi Hsu
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 7:45 Topological Representations in Functional Neuroimaging
Tristan Yates
Workshop
Fri 9:04 Computationally Accelerating Protein-Ligand Docking for Neglected Tropical Diseases: a case study on Drug Repurposing for Leishmaniasis
Hassan Kane
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
Fri 14:00 ML and Language (#2)