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Papers

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Probing Emergent Semantics in Predictive Agents via Question Answering
Abhishek Das, Federico Carnevale, Hamza Merzic et al.
2020 ICML
Problems with Shapley-value-based explanations as feature importance measures
I. Elizabeth Kumar, Suresh Venkatasubramanian, Carlos Scheidegger et al.
2020 ICML
Progressive Graph Learning for Open-Set Domain Adaptation
Yadan Luo, Zijian Wang, Zi Huang et al.
2020 ICML
2020 ICML
Projective Preferential Bayesian Optimization
Petrus Mikkola, Milica Todorović, Jari Järvi et al.
2020 ICML
Proper Network Interpretability Helps Adversarial Robustness in Classification
Akhilan Boopathy, Sijia Liu, Gaoyuan Zhang et al.
2020 ICML
2020 ICML
Provably Efficient Exploration in Policy Optimization
Qi Cai, Zhuoran Yang, Chi Jin et al.
2020 ICML
Provably Efficient Model-based Policy Adaptation
Yuda Song, Aditi Mavalankar, Wen Sun et al.
2020 ICML
Proving the Lottery Ticket Hypothesis: Pruning is All You Need
Eran Malach, Gilad Yehudai, Shai Shalev-Schwartz et al.
2020 ICML
2020 ICML
Quantized Decentralized Stochastic Learning over Directed Graphs
Hossein Taheri, Aryan Mokhtari, Hamed Hassani et al.
2020 ICML
Quantum Boosting
Srinivasan Arunachalam, Reevu Maity
2020 ICML
Quantum Expectation-Maximization for Gaussian mixture models
Iordanis Kerenidis, Alessandro Luongo, Anupam Prakash
2020 ICML
Q-value Path Decomposition for Deep Multiagent Reinforcement Learning
Yaodong Yang, Jianye Hao, Guangyong Chen et al.
2020 ICML
R2-B2: Recursive Reasoning-Based Bayesian Optimization for No-Regret Learning in Games
Zhongxiang Dai, Yizhou Chen, Bryan Kian Hsiang Low et al.
2020 ICML
Radioactive data: tracing through training
Alexandre Sablayrolles, Matthijs Douze, Cordelia Schmid et al.
2020 ICML
Random extrapolation for primal-dual coordinate descent
Ahmet Alacaoglu, Olivier Fercoq, Volkan Cevher
2020 ICML