7 citations · 11 across the 7 of their papers we have counts for
7 papers
Variance Alignment Score: A Simple But Tough-to-Beat Data Selection Method for Multimodal Contrastive Learning
Yiping Wang, Yifang Chen, Wendan Yan +2
In recent years, data selection has emerged as a core issue for large-scale visual-language model pretraining, especially on noisy web-curated datasets. One widely adopted strategy…
Optimal Exploration is no harder than Thompson Sampling
Zhaoqi Li, Kevin Jamieson, Lalit Jain
Given a set of arms and an unknown parameter vector , the pure exploration linear bandit problem aims to return $\arg\max_{…
Pick Planning Strategies for Large-Scale Package Manipulation
Shuai Li, Azarakhsh Keipour, Kevin Jamieson +4
Automating warehouse operations can reduce logistics overhead costs, ultimately driving down the final price for consumers, increasing the speed of delivery, and enhancing the resi…
Improved Active Multi-Task Representation Learning via Lasso
Yiping Wang, Yifang Chen, Kevin Jamieson +1
To leverage the copious amount of data from source tasks and overcome the scarcity of the target task samples, representation learning based on multi-task pretraining has become a…
Instance-dependent Sample Complexity Bounds for Zero-sum Matrix Games
Arnab Maiti, Kevin Jamieson, Lillian J. Ratliff
We study the sample complexity of identifying an approximate equilibrium for two-player zero-sum matrix games. That is, in a sequence of repeated game plays, how many r…
Comparing Human-Centric and Robot-Centric Sampling for Robot Deep Learning from Demonstrations
Michael Laskey, Caleb Chuck, Jonathan Lee +5
Motivated by recent advances in Deep Learning for robot control, this paper considers two learning algorithms in terms of how they acquire demonstrations. "Human-Centric" (HC) samp…