Education
Reward learning from human preferences and demonstrations in Atari
Borja Ibarz, Jan Leike, Tobias Pohlen, Geoffrey Irving, Shane Legg, Dario Amodei
Neural Information Processing Systems http://nips.cc/
Counterfactual Fairness by Combining Factual and Counterfactual Predictions
Counterfactual Fairness (CF), which posits that an ML model's outcome on any individual should remain unchanged if they had belonged to a different demographic
55576bcdf386ba73859fb71766f85758-Paper-Conference.pdf
Unsupervised skill discovery is a learning paradigm that aims to acquire diverse behaviors without explicit rewards.
Stepping on the Edge: Curvature A ware Learning Rate Tuners
(Liu and Nocedal, 1989). Similar efforts have been made for Polyak stepsizes (Berrada et al., 2020; Loizou et al., 2021), in addition to new methods which combine distance to optimality with online learning convergence bounds (Cutkosky et al., 2023; Classically-inspired methods, however, have generally struggled to gain traction in deep learning.
Glance and Focus: Memory Prompting for Multi-Event Video Question Answering Ziyi Bai
Video Question Answering (VideoQA) has emerged as a vital tool to evaluate agents' ability to understand human daily behaviors. Despite the recent success of large vision language models in many multi-modal tasks, complex situation reasoning over videos involving multiple human-object interaction events still remains challenging.
Causal Inference with Noisy and Missing Covariates via Matrix Factorization
Nathan Kallus, Xiaojie Mao, Madeleine Udell
Neural Information Processing Systems http://nips.cc/
