activity
20172026
most citedContinual Learning as Computationally Constrained Reinforcement Learning

2 citations · 2 across the 4 of their papers we have counts for

collaborators

5 papers

cs.LG2026

SAGG: Sample-Adaptive Gradient Gating for Robust Multimodal Learning under Heterogeneous Corruption

Wentao Zhang, Yifan Zhu, Yutong Zhang +1

Multimodal gradient balancing methods modulate encoder gradients with a shared scalar per modality, implicitly assuming that corruption is uniform across the training batch. In pra…

cs.DS2026

One-Shot Klein Cutting Planes for Lipschitz Geodesically Convex Optimization in Hyperbolic Space

Yutong Zhang, Yaoran Yang, Yifan Zhu +1

Motivated by the COLT 2023 open problem of Criscitiello, Martínez-Rubio, and Boumal on deterministic first-order methods for Lipschitz geodesically convex optimization on Hadamard…

cs.LG2023★ 2 cited

Continual Learning as Computationally Constrained Reinforcement Learning

Saurabh Kumar, Henrik Marklund, Ashish Rao +4

An agent that efficiently accumulates knowledge to develop increasingly sophisticated skills over a long lifetime could advance the frontier of artificial intelligence capabilities…

cs.LG2022

Is Stochastic Gradient Descent Near Optimal?

Yifan Zhu, Hong Jun Jeon, Benjamin Van Roy

The success of neural networks over the past decade has established them as effective models for many relevant data generating processes. Statistical theory on neural networks indi…

cs.GT2017

The Asymmetric Colonel Blotto Game

Simon Rubinstein-Salzedo, Yifan Zhu

This paper explores the Nash equilibria of a variant of the Colonel Blotto game, which we call the Asymmetric Colonel Blotto game. In the Colonel Blotto game, two players simultane…