Performance Analysis
Discrete-Smoothness in Online Algorithms with Predictions
The field of learning-augmented online algorithms has gained rapid prominence in recent years.
Graph Neural Flows for Unveiling Systemic Interactions Among Irregularly Sampled Time Series
Interacting systems are prevalent in nature.
Single-Loop Stochastic Algorithms for Difference of Max-Structured Weakly Convex Functions
Both component functions are in expectation forms, i.e.,
Self-Calibrated Tuning of Vision-Language Models for Out-of-Distribution Detection Geng Y u
The code is publicly available at: https://github.com/tmlr-group/SCT .
Bileve: Securing Text Provenance in Large Language Models Against Spoofing with Bi-level Signature
Text watermarks for large language models (LLMs) have been commonly used to identify the origins of machine-generated content, which is promising for assessing liability when combating deepfake or harmful content.
Distribution-Free Statistical Dispersion Control for Societal Applications
Previous work has focused mainly on bounding either the expected loss of a predictor or the probability that an individual prediction will incur a loss value in a specified range.
Adaptive Uncertainty Estimation via High-Dimensional Testing on Latent Representations
Uncertainty estimation aims to evaluate the confidence of a trained deep neural network.
EgoChoir: Capturing 3D H uman-O bject Interaction Regions from Egocentric Views Y uhang Y ang
For the egocentric HOI, in addition to perceiving semantics e.g., "what" interaction is occurring, capturing "where" the interaction specifically manifests in 3D space is