Search Results for author: Supriyo Ghosh

Found 8 papers, 1 papers with code

Dependency Aware Incident Linking in Large Cloud Systems

no code implementations5 Feb 2024 Supriyo Ghosh, Karish Grover, Jimmy Wong, Chetan Bansal, Rakesh Namineni, Mohit Verma, Saravan Rajmohan

In this paper, we propose the dependency-aware incident linking (DiLink) framework which leverages both textual and service dependency graph information to improve the accuracy and coverage of incident links not only coming from same service, but also from different services and workloads.

Automated Root Causing of Cloud Incidents using In-Context Learning with GPT-4

no code implementations24 Jan 2024 Xuchao Zhang, Supriyo Ghosh, Chetan Bansal, Rujia Wang, Minghua Ma, Yu Kang, Saravan Rajmohan

The results reveal that our in-context learning approach outperforms the previous fine-tuned large language models such as GPT-3 by an average of 24. 8\% across all metrics, with an impressive 49. 7\% improvement over the zero-shot model.

In-Context Learning

Deep Offline Reinforcement Learning for Real-world Treatment Optimization Applications

no code implementations15 Feb 2023 Milashini Nambiar, Supriyo Ghosh, Priscilla Ong, Yu En Chan, Yong Mong Bee, Pavitra Krishnaswamy

There is increasing interest in data-driven approaches for recommending optimal treatment strategies in many chronic disease management and critical care applications.

Decision Making Management +4

Recommending Root-Cause and Mitigation Steps for Cloud Incidents using Large Language Models

no code implementations10 Jan 2023 Toufique Ahmed, Supriyo Ghosh, Chetan Bansal, Thomas Zimmermann, Xuchao Zhang, Saravan Rajmohan

In this work, we do the first large-scale study to evaluate the effectiveness of these models for helping engineers root cause and mitigate production incidents.

Management Question Answering +1

Neural-Progressive Hedging: Enforcing Constraints in Reinforcement Learning with Stochastic Programming

no code implementations27 Feb 2022 Supriyo Ghosh, Laura Wynter, Shiau Hong Lim, Duc Thien Nguyen

We propose a framework, called neural-progressive hedging (NP), that leverages stochastic programming during the online phase of executing a reinforcement learning (RL) policy.

Portfolio Optimization reinforcement-learning +1

Picking Pearl From Seabed: Extracting Artefacts from Noisy Issue Triaging Collaborative Conversations for Hybrid Cloud Services

no code implementations31 May 2021 Amar Prakash Azad, Supriyo Ghosh, Ajay Gupta, Harshit Kumar, Prateeti Mohapatra

We propose a combination of unsupervised and supervised model with minimum human intervention that leverages domain knowledge to predict artefacts for a small amount of conversation data and use that for fine-tuning an already pretrained language model for artefact prediction on a large amount of conversation data.

Language Modelling

A Deep Ensemble Multi-Agent Reinforcement Learning Approach for Air Traffic Control

no code implementations3 Apr 2020 Supriyo Ghosh, Sean Laguna, Shiau Hong Lim, Laura Wynter, Hasan Poonawala

Air traffic control is an example of a highly challenging operational problem that is readily amenable to human expertise augmentation via decision support technologies.

Decision Making Management +3

Assessment of Vacancy Formation and Surface Energies of Materials using Classical Force-Fields

1 code implementation3 Apr 2018 Kamal Choudhary, Adam J. Biacchi, Supriyo Ghosh, Lucas Hale, Angela R. Hight Walker, Francesca Tavazza

Using some of the example cases, we show how our data can be used to directly compare different FFs for a material and to interpret experimental findings such as using Wulff construction for predicting equilibrium shape of nanoparticles.

Materials Science

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