8 citations · 8 across the 3 of their papers we have counts for
4 papers
Rotation-Based Subspace Tracking for Robust Kernel PCA on Streaming Data
Kris Lokere, John Fossaceca
Machine learning models process large amounts of data, and Principal Component Analysis (PCA) is a widely used technique to reduce the dimensionality of the data and extract useful…
EvalStop: Using World Feedback to Detect and Correct Reward Overoptimization in Multi-Tenant RLHF Platforms
Guilin Zhang, Chuanyi Sun, Kai Zhao +3
Cloud LLM fine-tuning platforms increasingly serve RLHF workloads, where a learned reward model is optimized as a proxy for human quality. As Gao et al. (2023) showed, this proxy d…
When Does Deep RL Beat Calibrated Baselines? A Benchmark Study on Adaptive Resource Control
Guilin Zhang, Chuanyi Sun, Kai Zhao +3
A properly calibrated rule-based autoscaler can beat every one of six mainstream deep reinforcement learning (DRL) algorithms on cost across every workload we test - so when, if ev…
Strategic Maneuver and Disruption with Reinforcement Learning Approaches for Multi-Agent Coordination
Derrik E. Asher, Anjon Basak, Rolando Fernandez +9
Reinforcement learning (RL) approaches can illuminate emergent behaviors that facilitate coordination across teams of agents as part of a multi-agent system (MAS), which can provid…