activity
20192026
most citedSageServe: Optimizing LLM Serving on Cloud Data Centers with Forecast Aware Auto-Scaling

3 citations · 12 across the 19 of their papers we have counts for

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Showing cs.LGShow all

5 papers · 1 filter

cs.LG2025

Attention Enhanced Entity Recommendation for Intelligent Monitoring in Cloud Systems

Fiza Husain, Anson Bastos, Anjaly Parayil +4

In this paper, we present DiRecGNN, an attention-enhanced entity recommendation framework for monitoring cloud services at Microsoft. We provide insights on the usefulness of this…

cs.LG2024

Ensuring Fair LLM Serving Amid Diverse Applications

Redwan Ibne Seraj Khan, Kunal Jain, Haiying Shen +12

In a multi-tenant large language model (LLM) serving platform hosting diverse applications, some users may submit an excessive number of requests, causing the service to become una…

cs.LG2024

Streetwise Agents: Empowering Offline RL Policies to Outsmart Exogenous Stochastic Disturbances in RTC

Aditya Soni, Mayukh Das, Anjaly Parayil +8

The difficulty of exploring and training online on real production systems limits the scope of real-time online data/feedback-driven decision making. The most feasible approach is…

cs.LG2022★ 1 cited

On the Hidden Biases of Policy Mirror Ascent in Continuous Action Spaces

Amrit Singh Bedi, Souradip Chakraborty, Anjaly Parayil +3

We focus on parameterized policy search for reinforcement learning over continuous action spaces. Typically, one assumes the score function associated with a policy is bounded, whi…

cs.LG2021★ 1 cited

On the Sample Complexity and Metastability of Heavy-tailed Policy Search in Continuous Control

Amrit Singh Bedi, Anjaly Parayil, Junyu Zhang +2

Reinforcement learning is a framework for interactive decision-making with incentives sequentially revealed across time without a system dynamics model. Due to its scaling to conti…