128 citations · 201 across the 16 of their papers we have counts for
16 papers
Leveraging Data Symmetries to Select an Optimal Subset of Training Data under Label Noise
Kumar Shubham, Pavan Karjol, Kiran M K +1
The performance of machine learning models often relies on large labeled datasets; however, data collected from diverse sources can contain label noise. Recent work has shown that,…
From Long Videos to Engaging Clips: A Human-Inspired Video Editing Framework with Multimodal Narrative Understanding
Xiangfeng Wang, Xiao Li, Yadong Wei +8
The rapid growth of online video content, especially on short video platforms, has created a growing demand for efficient video editing techniques that can condense long-form video…
In-Context Former: Lightning-fast Compressing Context for Large Language Model
Xiangfeng Wang, Zaiyi Chen, Zheyong Xie +3
With the rising popularity of Transformer-based large language models (LLMs), reducing their high inference costs has become a significant research focus. One effective approach is…
Boosting Gradient Ascent for Continuous DR-submodular Maximization
Qixin Zhang, Zongqi Wan, Zengde Deng +4
Projected Gradient Ascent (PGA) is the most commonly used optimization scheme in machine learning and operations research areas. Nevertheless, numerous studies and examples have sh…
An Online Algorithm for Chance Constrained Resource Allocation
Yuwei Chen, Zengde Deng, Yinzhi Zhou +3
This paper studies the online stochastic resource allocation problem (RAP) with chance constraints. The online RAP is a 0-1 integer linear programming problem where the resource co…
Communication-Efficient Decentralized Online Continuous DR-Submodular Maximization
Qixin Zhang, Zengde Deng, Xiangru Jian +3
Maximizing a monotone submodular function is a fundamental task in machine learning, economics, and statistics. In this paper, we present two communication-efficient decentralized…