Saravan Rajmohan
Orcid: 0009-0003-0204-7187
According to our database1,
Saravan Rajmohan
authored at least 68 papers
between 2022 and 2024.
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Bibliography
2024
Turn Every Application into an Agent: Towards Efficient Human-Agent-Computer Interaction with API-First LLM-Based Agents.
CoRR, 2024
Intelligent Router for LLM Workloads: Improving Performance Through Workload-Aware Scheduling.
CoRR, 2024
AgentGen: Enhancing Planning Abilities for Large Language Model based Agent via Environment and Task Generation.
CoRR, 2024
Thread: A Logic-Based Data Organization Paradigm for How-To Question Answering with Retrieval Augmented Generation.
CoRR, 2024
An Advanced Reinforcement Learning Framework for Online Scheduling of Deferrable Workloads in Cloud Computing.
CoRR, 2024
Large Language Models can Deliver Accurate and Interpretable Time Series Anomaly Detection.
CoRR, 2024
Lean Attention: Hardware-Aware Scalable Attention Mechanism for the Decode-Phase of Transformers.
CoRR, 2024
AllHands: Ask Me Anything on Large-scale Verbatim Feedback via Large Language Models.
CoRR, 2024
Why does Prediction Accuracy Decrease over Time? Uncertain Positive Learning for Cloud Failure Prediction.
CoRR, 2024
COIN: Chance-Constrained Imitation Learning for Uncertainty-aware Adaptive Resource Oversubscription Policy.
CoRR, 2024
Risk-aware Adaptive Virtual CPU Oversubscription in Microsoft Cloud via Prototypical Human-in-the-loop Imitation Learning.
CoRR, 2024
Revisiting VAE for Unsupervised Time Series Anomaly Detection: A Frequency Perspective.
Proceedings of the ACM on Web Conference 2024, 2024
Proceedings of the Companion Proceedings of the ACM on Web Conference 2024, 2024
LM-PACE: Confidence Estimation by Large Language Models for Effective Root Causing of Cloud Incidents.
Proceedings of the Companion Proceedings of the 32nd ACM International Conference on the Foundations of Software Engineering, 2024
Proceedings of the Companion Proceedings of the 32nd ACM International Conference on the Foundations of Software Engineering, 2024
Proceedings of the Companion Proceedings of the 32nd ACM International Conference on the Foundations of Software Engineering, 2024
Proceedings of the Companion Proceedings of the 32nd ACM International Conference on the Foundations of Software Engineering, 2024
Proceedings of the Companion Proceedings of the 32nd ACM International Conference on the Foundations of Software Engineering, 2024
Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2024
Proceedings of the 46th IEEE/ACM International Conference on Software Engineering, 2024
Proceedings of the 46th International Conference on Software Engineering: Software Engineering in Practice, 2024
Xpert: Empowering Incident Management with Query Recommendations via Large Language Models.
Proceedings of the 46th IEEE/ACM International Conference on Software Engineering, 2024
Proceedings of the Nineteenth European Conference on Computer Systems, 2024
Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing, 2024
AutoRAG-HP: Automatic Online Hyper-Parameter Tuning for Retrieval-Augmented Generation.
Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2024, 2024
Proceedings of the ECAI 2024 - 27th European Conference on Artificial Intelligence, 19-24 October 2024, Santiago de Compostela, Spain, 2024
Proceedings of the 2024 ACM Symposium on Cloud Computing, 2024
COIN: Chance-Constrained Imitation Learning for Safe and Adaptive Resource Oversubscription under Uncertainty.
Proceedings of the 33rd ACM International Conference on Information and Knowledge Management, 2024
Proceedings of the Findings of the Association for Computational Linguistics, 2024
Call Me When Necessary: LLMs can Efficiently and Faithfully Reason over Structured Environments.
Proceedings of the Findings of the Association for Computational Linguistics, 2024
2023
ImDiffusion: Imputed Diffusion Models for Multivariate Time Series Anomaly Detection.
Proc. VLDB Endow., November, 2023
Rethinking Privacy in Machine Learning Pipelines from an Information Flow Control Perspective.
CoRR, 2023
PACE-LM: Prompting and Augmentation for Calibrated Confidence Estimation with GPT-4 in Cloud Incident Root Cause Analysis.
CoRR, 2023
CoRR, 2023
Empowering Practical Root Cause Analysis by Large Language Models for Cloud Incidents.
CoRR, 2023
Learning Cooperative Oversubscription for Cloud by Chance-Constrained Multi-Agent Reinforcement Learning.
Proceedings of the ACM Web Conference 2023, 2023
Proceedings of the Companion Proceedings of the ACM Web Conference 2023, 2023
Multi-Agent Reinforcement Learning with Shared Policy for Cloud Quota Management Problem.
Proceedings of the Companion Proceedings of the ACM Web Conference 2023, 2023
Diffusion-Based Time Series Data Imputation for Cloud Failure Prediction at Microsoft 365.
Proceedings of the 31st ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering, 2023
Proceedings of the 31st ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering, 2023
Proceedings of the 31st ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering, 2023
TraceDiag: Adaptive, Interpretable, and Efficient Root Cause Analysis on Large-Scale Microservice Systems.
Proceedings of the 31st ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering, 2023
Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2023
Root Cause Analysis for Microservice Systems via Hierarchical Reinforcement Learning from Human Feedback.
Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2023
CODEC: Cost-Effective Duration Prediction System for Deadline Scheduling in the Cloud.
Proceedings of the 34th IEEE International Symposium on Software Reliability Engineering, 2023
TraceArk: Towards Actionable Performance Anomaly Alerting for Online Service Systems.
Proceedings of the 45th IEEE/ACM International Conference on Software Engineering: Software Engineering in Practice, 2023
Proceedings of the 45th IEEE/ACM International Conference on Software Engineering, 2023
Proceedings of the 45th IEEE/ACM International Conference on Software Engineering: Software Engineering in Practice, 2023
Recommending Root-Cause and Mitigation Steps for Cloud Incidents using Large Language Models.
Proceedings of the 45th IEEE/ACM International Conference on Software Engineering, 2023
Proceedings of the Eleventh International Conference on Learning Representations, 2023
Empower Large Language Model to Perform Better on Industrial Domain-Specific Question Answering.
Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing: EMNLP 2023, 2023
How Different are the Cloud Workloads? Characterizing Large-Scale Private and Public Cloud Workloads.
Proceedings of the 53rd Annual IEEE/IFIP International Conference on Dependable Systems and Network, 2023
Proceedings of the 28th ACM International Conference on Architectural Support for Programming Languages and Operating Systems, 2023
2022
An Intelligent Framework for Timely, Accurate, and Comprehensive Cloud Incident Detection.
ACM SIGOPS Oper. Syst. Rev., 2022
Proceedings of the Companion of The Web Conference 2022, Virtual Event / Lyon, France, April 25, 2022
Proceedings of the WWW '22: The ACM Web Conference 2022, Virtual Event, Lyon, France, April 25, 2022
Solving the Batch Stochastic Bin Packing Problem in Cloud: A Chance-constrained Optimization Approach.
Proceedings of the KDD '22: The 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, Washington, DC, USA, August 14, 2022
NENYA: Cascade Reinforcement Learning for Cost-Aware Failure Mitigation at Microsoft 365.
Proceedings of the KDD '22: The 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, Washington, DC, USA, August 14, 2022
Multi-task Hierarchical Classification for Disk Failure Prediction in Online Service Systems.
Proceedings of the KDD '22: The 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, Washington, DC, USA, August 14, 2022
T-SMOTE: Temporal-oriented Synthetic Minority Oversampling Technique for Imbalanced Time Series Classification.
Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence, 2022