1 citations · 1 across the 5 of their papers we have counts for
7 papers · 1 filter
The price of multi-group transductive learning
Noah Bergam, Samuel Deng, Daniel Hsu
We show every multi-group learner in the transductive setting may incur a multiplicative penalty in its error rate on some group relative to the error rate achievable in the single…
A One-Inclusion Graph Approach to Multi-Group Learning
Noah Bergam, Samuel Deng, Daniel Hsu
We prove the tightest-known upper bounds on the sample complexity of multi-group learning. Our algorithm extends the one-inclusion graph prediction strategy using a generalization…
Group-realizable multi-group learning by minimizing empirical risk
Navid Ardeshir, Samuel Deng, Daniel Hsu +1
The sample complexity of multi-group learning is shown to improve in the group-realizable setting over the agnostic setting, even when the family of groups is infinite so long as i…
Group-wise oracle-efficient algorithms for online multi-group learning
Samuel Deng, Daniel Hsu, Jingwen Liu
We study the problem of online multi-group learning, a learning model in which an online learner must simultaneously achieve small prediction regret on a large collection of (possi…
Multi-group Learning for Hierarchical Groups
Samuel Deng, Daniel Hsu
The multi-group learning model formalizes the learning scenario in which a single predictor must generalize well on multiple, possibly overlapping subgroups of interest. We extend…
Learning Tensor Representations for Meta-Learning
Samuel Deng, Yilin Guo, Daniel Hsu +1
We introduce a tensor-based model of shared representation for meta-learning from a diverse set of tasks. Prior works on learning linear representations for meta-learning assume th…