159 citations · 798 across the 116 of their papers we have counts for
14 papers · 1 filter
Decision-Aware Learning for Optimizing Health Supply Chains
Tsai-Hsuan Chung, Vahid Rostami, Hamsa Bastani +1
We study the problem of allocating limited supply of medical resources in developing countries, in particular, Sierra Leone. We address this problem by combining machine learning (…
Bandits for Online Calibration: An Application to Content Moderation on Social Media Platforms
Vashist Avadhanula, Omar Abdul Baki, Hamsa Bastani +17
We describe the current content moderation strategy employed by Meta to remove policy-violating content from its platforms. Meta relies on both handcrafted and learned risk models…
ACon: Adaptive Conformal Consensus for Provable Blockchain Oracles
Sangdon Park, Osbert Bastani, Taesoo Kim
Blockchains with smart contracts are distributed ledger systems that achieve block-state consistency among distributed nodes by only allowing deterministic operations of smart cont…
Regret Bounds for Risk-Sensitive Reinforcement Learning
O. Bastani, Y. J. Ma, E. Shen +1
In safety-critical applications of reinforcement learning such as healthcare and robotics, it is often desirable to optimize risk-sensitive objectives that account for tail outcome…
VIP: Towards Universal Visual Reward and Representation via Value-Implicit Pre-Training
Yecheng Jason Ma, Shagun Sodhani, Dinesh Jayaraman +3
Reward and representation learning are two long-standing challenges for learning an expanding set of robot manipulation skills from sensory observations. Given the inherent cost an…
PAC Prediction Sets for Meta-Learning
Sangdon Park, Edgar Dobriban, Insup Lee +1
Uncertainty quantification is a key component of machine learning models targeted at safety-critical systems such as in healthcare or autonomous vehicles. We study this problem in…