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Papers

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Oops I Took A Gradient: Scalable Sampling for Discrete Distributions
Will Grathwohl, Kevin Swersky, Milad Hashemi et al.
2021 ICML
Operationalizing Complex Causes: A Pragmatic View of Mediation
Limor Gultchin, David Watson, Matt Kusner et al.
2021 ICML
Optimal Complexity in Decentralized Training
Yucheng Lu, Christopher De Sa
2021 ICML
2021 ICML
Optimal Off-Policy Evaluation from Multiple Logging Policies
Nathan Kallus, Yuta Saito, Masatoshi Uehara
2021 ICML
Optimal regret algorithm for Pseudo-1d Bandit Convex Optimization
Aadirupa Saha, Nagarajan Natarajan, Praneeth Netrapalli et al.
2021 ICML
Optimal Streaming Algorithms for Multi-Armed Bandits
Tianyuan Jin, Keke Huang, Jing Tang et al.
2021 ICML
Optimal Thompson Sampling strategies for support-aware CVaR bandits
Dorian Baudry, Romain Gautron, Emilie Kaufmann et al.
2021 ICML
Optimization Planning for 3D ConvNets
Zhaofan Qiu, Ting Yao, Chong-Wah Ngo et al.
2021 ICML
Optimizing Black-box Metrics with Iterative Example Weighting
Gaurush Hiranandani, Jatin Mathur, Harikrishna Narasimhan et al.
2021 ICML
Optimizing persistent homology based functions
Mathieu Carriere, Frederic Chazal, Marc Glisse et al.
2021 ICML
2021 ICML
Outlier-Robust Optimal Transport
Debarghya Mukherjee, Aritra Guha, Justin M Solomon et al.
2021 ICML
Out-of-Distribution Generalization via Risk Extrapolation (REx)
David Krueger, Ethan Caballero, Joern-Henrik Jacobsen et al.
2021 ICML
Outside the Echo Chamber: Optimizing the Performative Risk
John P Miller, Juan C Perdomo, Tijana Zrnic
2021 ICML
2021 ICML
PAC-Learning for Strategic Classification
Ravi Sundaram, Anil Vullikanti, Haifeng Xu et al.
2021 ICML
PACOH: Bayes-Optimal Meta-Learning with PAC-Guarantees
Jonas Rothfuss, Vincent Fortuin, Martin Josifoski et al.
2021 ICML