Summary of Tight Bounds For Online Convex Optimization with Adversarial Constraints, by Abhishek Sinha and Rahul Vaze
Tight Bounds for Online Convex Optimization with Adversarial Constraintsby Abhishek Sinha, Rahul VazeFirst submitted to…
Tight Bounds for Online Convex Optimization with Adversarial Constraintsby Abhishek Sinha, Rahul VazeFirst submitted to…
Agnostic Active Learning of Single Index Models with Linear Sample Complexityby Aarshvi Gajjar, Wai Ming…
Gradient Boosted Filters For Signal Processingby Jose A. Lopez, Georg Stemmer, Hector A. CordourierFirst submitted…
The Pitfalls and Promise of Conformal Inference Under Adversarial Attacksby Ziquan Liu, Yufei Cui, Yan…
Large Language Models for Human-Machine Collaborative Particle Accelerator Tuning through Natural Languageby Jan Kaiser, Annika…
RS-Reg: Probabilistic and Robust Certified Regression Through Randomized Smoothingby Aref Miri Rekavandi, Olga Ohrimenko, Benjamin…
CLIP with Quality Captions: A Strong Pretraining for Vision Tasksby Pavan Kumar Anasosalu Vasu, Hadi…
Feature Importance and Explainability in Quantum Machine Learningby Luke Power, Krishnendu GuhaFirst submitted to arxiv…
Neural Active Learning Meets the Partial Monitoring Frameworkby Maxime Heuillet, Ola Ahmad, Audrey DurandFirst submitted…
Neural Collapse Meets Differential Privacy: Curious Behaviors of NoisyGD with Near-perfect Representation Learningby Chendi Wang,…