• case-insensitive prefix search: default
  e.g., sig matches "SIGIR" as well as "signal"
• exact word search: append dollar sign ($) to word
  e.g., graph$ matches "graph", but not "graphics"
• boolean and: separate words by space
  e.g., codd model
• boolean or: connect words by pipe symbol (|)
  e.g., graph|network

Update May 7, 2017: Please note that we had to disable the phrase search operator (.) and the boolean not operator (-) due to technical problems. For the time being, phrase search queries will yield regular prefix search result, and search terms preceded by a minus will be interpreted as regular (positive) search terms.

found 775 matches

• 2019
• 
  Xi Peng, Zhenyu Huang, Jiancheng Lv, Hongyuan Zhu, Joey Tianyi Zhou:
  COMIC: Multi-view Clustering Without Parameter Selection. ICML 2019: 5092-5101
• 
  Ehsan Kazemi, Marko Mitrovic, Morteza Zadimoghaddam, Silvio Lattanzi, Amin Karbasi:
  Submodular Streaming in All Its Glory: Tight Approximation, Minimum Memory and Low Adaptive Complexity. ICML 2019: 3311-3320
• 
  Ravi Kumar, Rina Panigrahy, Ali Rahimi, David P. Woodruff:
  Faster Algorithms for Binary Matrix Factorization. ICML 2019: 3551-3559
• 
  Han Zhao, Remi Tachet des Combes, Kun Zhang, Geoffrey J. Gordon:
  On Learning Invariant Representations for Domain Adaptation. ICML 2019: 7523-7532
• 
  Donghwan Lee, Niao He:
  Target-Based Temporal-Difference Learning. ICML 2019: 3713-3722
• 
  Tian Guo, Tao Lin, Nino Antulov-Fantulin:
  Exploring interpretable LSTM neural networks over multi-variable data. ICML 2019: 2494-2504
• 
  Yuchen Zhang, Tianle Liu, Mingsheng Long, Michael I. Jordan:
  Bridging Theory and Algorithm for Domain Adaptation. ICML 2019: 7404-7413
• 
  Wen Sun, Anirudh Vemula, Byron Boots, Drew Bagnell:
  Provably Efficient Imitation Learning from Observation Alone. ICML 2019: 6036-6045
• 
  Hoang Minh Le, Cameron Voloshin, Yisong Yue:
  Batch Policy Learning under Constraints. ICML 2019: 3703-3712
• 
  Taisuke Yasuda, David P. Woodruff, Manuel Fernandez:
  Tight Kernel Query Complexity of Kernel Ridge Regression and Kernel $k$-means Clustering. ICML 2019: 7055-7063
• 
  Ryota Suzuki, Ryusuke Takahama, Shun Onoda:
  Hyperbolic Disk Embeddings for Directed Acyclic Graphs. ICML 2019: 6066-6075
• 
  Gabriele Abbati, Philippe Wenk, Michael A. Osborne, Andreas Krause, Bernhard Schölkopf, Stefan Bauer:
  AReS and MaRS Adversarial and MMD-Minimizing Regression for SDEs. ICML 2019: 1-10
• 
  Axel Abels, Diederik M. Roijers, Tom Lenaerts, Ann Nowé, Denis Steckelmacher:
  Dynamic Weights in Multi-Objective Deep Reinforcement Learning. ICML 2019: 11-20
• 
  Sami Abu-El-Haija, Bryan Perozzi, Amol Kapoor, Nazanin Alipourfard, Kristina Lerman, Hrayr Harutyunyan, Greg Ver Steeg, Aram Galstyan:
  MixHop: Higher-Order Graph Convolutional Architectures via Sparsified Neighborhood Mixing. ICML 2019: 21-29
• 
  Jayadev Acharya, Clément L. Canonne, Himanshu Tyagi:
  Communication-Constrained Inference and the Role of Shared Randomness. ICML 2019: 30-39
• 
  Jayadev Acharya, Ziteng Sun:
  Communication Complexity in Locally Private Distribution Estimation and Heavy Hitters. ICML 2019: 51-60
• 
  Jayadev Acharya, Chris De Sa, Dylan J. Foster, Karthik Sridharan:
  Distributed Learning with Sublinear Communication. ICML 2019: 40-50
• 
  Roy Adams, Yuelong Ji, Xiaobin Wang, Suchi Saria:
  Learning Models from Data with Measurement Error: Tackling Underreporting. ICML 2019: 61-70
• 
  Tameem Adel, Adrian Weller:
  TibGM: A Transferable and Information-Based Graphical Model Approach for Reinforcement Learning. ICML 2019: 71-81
• 
  Abhijin Adiga, Chris J. Kuhlman, Madhav V. Marathe, S. S. Ravi, Anil Vullikanti:
  PAC Learnability of Node Functions in Networked Dynamical Systems. ICML 2019: 82-91
• 
  Ashish Agarwal:
  Static Automatic Batching In TensorFlow. ICML 2019: 92-101
• 
  Naman Agarwal, Brian Bullins, Xinyi Chen, Elad Hazan, Karan Singh, Cyril Zhang, Yi Zhang:
  Efficient Full-Matrix Adaptive Regularization. ICML 2019: 102-110
• 
  Naman Agarwal, Brian Bullins, Elad Hazan, Sham M. Kakade, Karan Singh:
  Online Control with Adversarial Disturbances. ICML 2019: 111-119
• 
  Alekh Agarwal, Miroslav Dudík, Zhiwei Steven Wu:
  Fair Regression: Quantitative Definitions and Reduction-Based Algorithms. ICML 2019: 120-129
• 
  Rishabh Agarwal, Chen Liang, Dale Schuurmans, Mohammad Norouzi:
  Learning to Generalize from Sparse and Underspecified Rewards. ICML 2019: 130-140
• 
  Raj Agrawal, Brian L. Trippe, Jonathan H. Huggins, Tamara Broderick:
  The Kernel Interaction Trick: Fast Bayesian Discovery of Pairwise Interactions in High Dimensions. ICML 2019: 141-150
• 
  Zafarali Ahmed, Nicolas Le Roux, Mohammad Norouzi, Dale Schuurmans:
  Understanding the Impact of Entropy on Policy Optimization. ICML 2019: 151-160
• 
  Ulrich Aïvodji, Hiromi Arai, Olivier Fortineau, Sébastien Gambs, Satoshi Hara, Alain Tapp:
  Fairwashing: the risk of rationalization. ICML 2019: 161-170
• 
  Youhei Akimoto, Shinichi Shirakawa, Nozomu Yoshinari, Kento Uchida, Shota Saito, Kouhei Nishida:
  Adaptive Stochastic Natural Gradient Method for One-Shot Neural Architecture Search. ICML 2019: 171-180
• 
  Riad Akrour, Joni Pajarinen, Jan Peters, Gerhard Neumann:
  Projections for Approximate Policy Iteration Algorithms. ICML 2019: 181-190

skipping 745 more matches