Mayukh Das

Senior Researcher

Papiers de Collaboration

Afficher par:

- ProtoRAIL: A Risk-cognizant Imitation Agent for Adaptive vCPU Oversubscription In The Cloud
  
  Lu Wang, Mayukh Das, Fangkai Yang, Bo Qiao, Hang Dong, Si Qin, Victor Ruehle, Chetan Bansal, Eli Cortez, Íñigo Goiri, Saravan Rajmohan, Qingwei Lin 林庆维, Dongmei Zhang
  
  MLSys'25 | May 2025
  
  Publication
- COIN: Chance-Constrained Imitation Learning for Safe and Adaptive Resource Oversubscription under Uncertainty
  
  Lu Wang, Mayukh Das, Fangkai Yang, Chao Du, Bo Qiao, Hang Dong, Chetan Bansal, Si Qin, Saravan Rajmohan, Qingwei Lin 林庆维, Dongmei Zhang, Qi Zhang
  
  CIKM'24 | October 2024
  
  PDF
- SmartOClock: Workload- and Risk-Aware Overclocking in the Cloud
  
  Jovan Stojkovic, Pulkit Misra, Íñigo Goiri, Sam Whitlock, Esha Choukse, Mayukh Das, Chetan Bansal, Jason Lee, Zoey Sun, Haoran Qiu, Reed Zimmermann, Savyasachi Samal, Brijesh Warrier, Ashish Raniwala, Ricardo Bianchini
  
  ISCA | June 2024
  
  Publication
- Intelligent Overclocking for Improved Cloud Efficiency
  
  Aditya Soni, Mayukh Das, Pulkit Misra, Chetan Bansal
  
  AIOps '24 workshop @ ASPLOS [5th International Workshop on Cloud Intelligence / AIOps] | April 2024
  
  Preprint
- OPPerTune: Post-Deployment Configuration Tuning of Services Made Easy
  
  Gagan Somashekar, Karan Tandon, Anush Kini, Chieh-Chun Chang, Petr Husak, Ranjita Bhagwan, Mayukh Das, Anshul Gandhi, Nagarajan Natarajan
  
  NSDI 2024 | April 2024
  
  Publication Publication Github Projet Projet
- NASerEx: Optimizing Early Exits via AutoML for Scalable Efficient Inference in Big Image Streams
  
  Aakash Kapoor, Rajath Elias Soans, Soham Dixit, Pradeep NS, Brijraj Singh, Mayukh Das
  
  IEEE Big Data 2023 | December 2023
  
  Special session on Machine Learning on Big Data (MLBD)
  
  Publication
- AutoCoMet: Smart Neural Architecture Search via Co-Regulated Shaping Reinforcement
  
  Mayukh Das, Brijraj Singh, Harsh Kanti Chheda, Pawan Sharma, Pradeep NS
  
  ICPR | August 2022
  
  Publication
- Beyond Simple Images: Human Knowledge-Guided GANs for Clinical Data Generation
  
  Devendra Singh Dhami, Mayukh Das, Sriraam Natarajan
  
  International Conference on Principles of Knowledge Representation and Reasoning (KR) | September 2021
  
  Publication
- Human-Guided Learning of Column Networks: Knowledge Injection for Relational Deep Learning
  
  Mayukh Das, Devendra Singh Dhami, Yang Yu, Gautam Kunapuli, Sriraam Natarajan
  
  CODS-COMAD | January 2021
  
  Publication
- Few-Shot Induction of Generalized Logical Concepts via Human Guidance
  
  Mayukh Das, Nandini Ramanan, Janardhan Rao Doppa, Sriraam Natarajan
  
  Frontiers in Robotics and AI | November 2020
  
  Publication
- Planning with actively eliciting preferences
  
  Mayukh Das, Phillip Odom, Md. Rakibul Islam, Janardhan Rao Doppa, Dan Roth, Sriraam Natarajan
  
  Knowledge Based Systems | February 2019, Vol 165: pp. 219-227
  
  Publication
- Fast Relational Probabilistic Inference and Learning: Approximate Counting via Hypergraphs
  
  Mayukh Das, Devendra Singh Dhami, Gautam Kunapuli, Kristian Kersting, Sriraam Natarajan
  
  AAAI | January 2019
  
  Publication
- Preference-Guided Planning: An Active Elicitation Approach
  
  Mayukh Das, Phillip Odom, Md. Rakibul Islam, Janardhan Rao Doppa, Dan Roth, Sriraam Natarajan
  
  17th International Conference on Autonomous Agents and MultiAgent Systems (AAMAS) | July 2018
  
  Publication Publication

- ProtoRAIL: A Risk-cognizant Imitation Agent for Adaptive vCPU Oversubscription In The Cloud
  
  Lu Wang, Mayukh Das, Fangkai Yang, Bo Qiao, Hang Dong, Si Qin, Victor Ruehle, Chetan Bansal, Eli Cortez, Íñigo Goiri, Saravan Rajmohan, Qingwei Lin 林庆维, Dongmei Zhang
  
  MLSys'25 | May 2025
  
  Publication
- COIN: Chance-Constrained Imitation Learning for Safe and Adaptive Resource Oversubscription under Uncertainty
  
  Lu Wang, Mayukh Das, Fangkai Yang, Chao Du, Bo Qiao, Hang Dong, Chetan Bansal, Si Qin, Saravan Rajmohan, Qingwei Lin 林庆维, Dongmei Zhang, Qi Zhang
  
  CIKM'24 | October 2024
  
  PDF
- Intelligent Overclocking for Improved Cloud Efficiency
  
  Aditya Soni, Mayukh Das, Pulkit Misra, Chetan Bansal
  
  AIOps '24 workshop @ ASPLOS [5th International Workshop on Cloud Intelligence / AIOps] | April 2024
  
  Preprint
- NASerEx: Optimizing Early Exits via AutoML for Scalable Efficient Inference in Big Image Streams
  
  Aakash Kapoor, Rajath Elias Soans, Soham Dixit, Pradeep NS, Brijraj Singh, Mayukh Das
  
  IEEE Big Data 2023 | December 2023
  
  Special session on Machine Learning on Big Data (MLBD)
  
  Publication
- AutoCoMet: Smart Neural Architecture Search via Co-Regulated Shaping Reinforcement
  
  Mayukh Das, Brijraj Singh, Harsh Kanti Chheda, Pawan Sharma, Pradeep NS
  
  ICPR | August 2022
  
  Publication
- Beyond Simple Images: Human Knowledge-Guided GANs for Clinical Data Generation
  
  Devendra Singh Dhami, Mayukh Das, Sriraam Natarajan
  
  International Conference on Principles of Knowledge Representation and Reasoning (KR) | September 2021
  
  Publication
- Human-Guided Learning of Column Networks: Knowledge Injection for Relational Deep Learning
  
  Mayukh Das, Devendra Singh Dhami, Yang Yu, Gautam Kunapuli, Sriraam Natarajan
  
  CODS-COMAD | January 2021
  
  Publication
- Few-Shot Induction of Generalized Logical Concepts via Human Guidance
  
  Mayukh Das, Nandini Ramanan, Janardhan Rao Doppa, Sriraam Natarajan
  
  Frontiers in Robotics and AI | November 2020
  
  Publication
- Planning with actively eliciting preferences
  
  Mayukh Das, Phillip Odom, Md. Rakibul Islam, Janardhan Rao Doppa, Dan Roth, Sriraam Natarajan
  
  Knowledge Based Systems | February 2019, Vol 165: pp. 219-227
  
  Publication
- Fast Relational Probabilistic Inference and Learning: Approximate Counting via Hypergraphs
  
  Mayukh Das, Devendra Singh Dhami, Gautam Kunapuli, Kristian Kersting, Sriraam Natarajan
  
  AAAI | January 2019
  
  Publication
- Preference-Guided Planning: An Active Elicitation Approach
  
  Mayukh Das, Phillip Odom, Md. Rakibul Islam, Janardhan Rao Doppa, Dan Roth, Sriraam Natarajan
  
  17th International Conference on Autonomous Agents and MultiAgent Systems (AAMAS) | July 2018
  
  Publication Publication
- ProtoRAIL: A Risk-cognizant Imitation Agent for Adaptive vCPU Oversubscription In The Cloud
  
  Lu Wang, Mayukh Das, Fangkai Yang, Bo Qiao, Hang Dong, Si Qin, Victor Ruehle, Chetan Bansal, Eli Cortez, Íñigo Goiri, Saravan Rajmohan, Qingwei Lin 林庆维, Dongmei Zhang
  
  MLSys'25 | May 2025
  
  Publication
- COIN: Chance-Constrained Imitation Learning for Safe and Adaptive Resource Oversubscription under Uncertainty
  
  Lu Wang, Mayukh Das, Fangkai Yang, Chao Du, Bo Qiao, Hang Dong, Chetan Bansal, Si Qin, Saravan Rajmohan, Qingwei Lin 林庆维, Dongmei Zhang, Qi Zhang
  
  CIKM'24 | October 2024
  
  PDF
- SmartOClock: Workload- and Risk-Aware Overclocking in the Cloud
  
  Jovan Stojkovic, Pulkit Misra, Íñigo Goiri, Sam Whitlock, Esha Choukse, Mayukh Das, Chetan Bansal, Jason Lee, Zoey Sun, Haoran Qiu, Reed Zimmermann, Savyasachi Samal, Brijesh Warrier, Ashish Raniwala, Ricardo Bianchini
  
  ISCA | June 2024
  
  Publication
- Intelligent Overclocking for Improved Cloud Efficiency
  
  Aditya Soni, Mayukh Das, Pulkit Misra, Chetan Bansal
  
  AIOps '24 workshop @ ASPLOS [5th International Workshop on Cloud Intelligence / AIOps] | April 2024
  
  Preprint
- OPPerTune: Post-Deployment Configuration Tuning of Services Made Easy
  
  Gagan Somashekar, Karan Tandon, Anush Kini, Chieh-Chun Chang, Petr Husak, Ranjita Bhagwan, Mayukh Das, Anshul Gandhi, Nagarajan Natarajan
  
  NSDI 2024 | April 2024
  
  Publication Publication Github Projet Projet
- NASerEx: Optimizing Early Exits via AutoML for Scalable Efficient Inference in Big Image Streams
  
  Aakash Kapoor, Rajath Elias Soans, Soham Dixit, Pradeep NS, Brijraj Singh, Mayukh Das
  
  IEEE Big Data 2023 | December 2023
  
  Special session on Machine Learning on Big Data (MLBD)
  
  Publication
- OPPerTune: Post-Deployment Configuration Tuning of Services Made Easy
  
  Gagan Somashekar, Karan Tandon, Anush Kini, Chieh-Chun Chang, Petr Husak, Ranjita Bhagwan, Mayukh Das, Anshul Gandhi, Nagarajan Natarajan
  
  NSDI 2024 | April 2024
  
  Publication Publication Github Projet Projet
- NASerEx: Optimizing Early Exits via AutoML for Scalable Efficient Inference in Big Image Streams
  
  Aakash Kapoor, Rajath Elias Soans, Soham Dixit, Pradeep NS, Brijraj Singh, Mayukh Das
  
  IEEE Big Data 2023 | December 2023
  
  Special session on Machine Learning on Big Data (MLBD)
  
  Publication
- Preference-Guided Planning: An Active Elicitation Approach
  
  Mayukh Das, Phillip Odom, Md. Rakibul Islam, Janardhan Rao Doppa, Dan Roth, Sriraam Natarajan
  
  17th International Conference on Autonomous Agents and MultiAgent Systems (AAMAS) | July 2018
  
  Publication Publication

- ProtoRAIL: A Risk-cognizant Imitation Agent for Adaptive vCPU Oversubscription In The Cloud
  
  Lu Wang, Mayukh Das, Fangkai Yang, Bo Qiao, Hang Dong, Si Qin, Victor Ruehle, Chetan Bansal, Eli Cortez, Íñigo Goiri, Saravan Rajmohan, Qingwei Lin 林庆维, Dongmei Zhang
  
  MLSys'25 | May 2025
  
  Publication
- COIN: Chance-Constrained Imitation Learning for Safe and Adaptive Resource Oversubscription under Uncertainty
  
  Lu Wang, Mayukh Das, Fangkai Yang, Chao Du, Bo Qiao, Hang Dong, Chetan Bansal, Si Qin, Saravan Rajmohan, Qingwei Lin 林庆维, Dongmei Zhang, Qi Zhang
  
  CIKM'24 | October 2024
  
  PDF
- SmartOClock: Workload- and Risk-Aware Overclocking in the Cloud
  
  Jovan Stojkovic, Pulkit Misra, Íñigo Goiri, Sam Whitlock, Esha Choukse, Mayukh Das, Chetan Bansal, Jason Lee, Zoey Sun, Haoran Qiu, Reed Zimmermann, Savyasachi Samal, Brijesh Warrier, Ashish Raniwala, Ricardo Bianchini
  
  ISCA | June 2024
  
  Publication
- Intelligent Overclocking for Improved Cloud Efficiency
  
  Aditya Soni, Mayukh Das, Pulkit Misra, Chetan Bansal
  
  AIOps '24 workshop @ ASPLOS [5th International Workshop on Cloud Intelligence / AIOps] | April 2024
  
  Preprint
- OPPerTune: Post-Deployment Configuration Tuning of Services Made Easy
  
  Gagan Somashekar, Karan Tandon, Anush Kini, Chieh-Chun Chang, Petr Husak, Ranjita Bhagwan, Mayukh Das, Anshul Gandhi, Nagarajan Natarajan
  
  NSDI 2024 | April 2024
  
  Publication Publication Github Projet Projet
- NASerEx: Optimizing Early Exits via AutoML for Scalable Efficient Inference in Big Image Streams
  
  Aakash Kapoor, Rajath Elias Soans, Soham Dixit, Pradeep NS, Brijraj Singh, Mayukh Das
  
  IEEE Big Data 2023 | December 2023
  
  Special session on Machine Learning on Big Data (MLBD)
  
  Publication
- AutoCoMet: Smart Neural Architecture Search via Co-Regulated Shaping Reinforcement
  
  Mayukh Das, Brijraj Singh, Harsh Kanti Chheda, Pawan Sharma, Pradeep NS
  
  ICPR | August 2022
  
  Publication
- Beyond Simple Images: Human Knowledge-Guided GANs for Clinical Data Generation
  
  Devendra Singh Dhami, Mayukh Das, Sriraam Natarajan
  
  International Conference on Principles of Knowledge Representation and Reasoning (KR) | September 2021
  
  Publication
- Human-Guided Learning of Column Networks: Knowledge Injection for Relational Deep Learning
  
  Mayukh Das, Devendra Singh Dhami, Yang Yu, Gautam Kunapuli, Sriraam Natarajan
  
  CODS-COMAD | January 2021
  
  Publication
- Fast Relational Probabilistic Inference and Learning: Approximate Counting via Hypergraphs
  
  Mayukh Das, Devendra Singh Dhami, Gautam Kunapuli, Kristian Kersting, Sriraam Natarajan
  
  AAAI | January 2019
  
  Publication
- Preference-Guided Planning: An Active Elicitation Approach
  
  Mayukh Das, Phillip Odom, Md. Rakibul Islam, Janardhan Rao Doppa, Dan Roth, Sriraam Natarajan
  
  17th International Conference on Autonomous Agents and MultiAgent Systems (AAMAS) | July 2018
  
  Publication Publication
- Few-Shot Induction of Generalized Logical Concepts via Human Guidance
  
  Mayukh Das, Nandini Ramanan, Janardhan Rao Doppa, Sriraam Natarajan
  
  Frontiers in Robotics and AI | November 2020
  
  Publication
- Planning with actively eliciting preferences
  
  Mayukh Das, Phillip Odom, Md. Rakibul Islam, Janardhan Rao Doppa, Dan Roth, Sriraam Natarajan
  
  Knowledge Based Systems | February 2019, Vol 165: pp. 219-227
  
  Publication