Summary of Distributionally Robust Policy Learning Under Concept Drifts, by Jingyuan Wang et al.
Distributionally Robust Policy Learning under Concept Driftsby Jingyuan Wang, Zhimei Ren, Ruohan Zhan, Zhengyuan ZhouFirst…
Distributionally Robust Policy Learning under Concept Driftsby Jingyuan Wang, Zhimei Ren, Ruohan Zhan, Zhengyuan ZhouFirst…
The Multiplex Classification Framework: optimizing multi-label classifiers through problem transformation, ontology engineering, and model ensemblingby…
What Has Been Overlooked in Contrastive Source-Free Domain Adaptation: Leveraging Source-Informed Latent Augmentation within Neighborhood…
Covariances for Free: Exploiting Mean Distributions for Federated Learning with Pre-Trained Modelsby Dipam Goswami, Simone…
On the Robustness of Spectral Algorithms for Semirandom Stochastic Block Modelsby Aditya Bhaskara, Agastya Vibhuti…
Stealing That Free Lunch: Exposing the Limits of Dyna-Style Reinforcement Learningby Brett Barkley, David Fridovich-KeilFirst…
Enabling Realtime Reinforcement Learning at Scale with Staggered Asynchronous Inferenceby Matthew Riemer, Gopeshh Subbaraj, Glen…
A Unifying Information-theoretic Perspective on Evaluating Generative Modelsby Alexis Fox, Samarth Swarup, Abhijin AdigaFirst submitted…
ResQ: Mixed-Precision Quantization of Large Language Models with Low-Rank Residualsby Utkarsh Saxena, Sayeh Sharify, Kaushik…
SEREP: Semantic Facial Expression Representation for Robust In-the-Wild Capture and Retargetingby Arthur Josi, Luiz Gustavo…