Mayukh Das

According to our database, Mayukh Das authored at least 31 papers between 2016 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2024

COIN: Chance-Constrained Imitation Learning for Uncertainty-aware Adaptive Resource Oversubscription Policy.

Lu Wang, Mayukh Das, Fangkai Yang, Chao Du, Bo Qiao, Hang Dong, Si Qin, Chetan Bansal, Qingwei Lin, Saravan Rajmohan, Dongmei Zhang, Qi Zhang

CoRR, 2024

Risk-aware Adaptive Virtual CPU Oversubscription in Microsoft Cloud via Prototypical Human-in-the-loop Imitation Learning.

Lu Wang, Mayukh Das, Fangkai Yang, Junjie Sheng, Bo Qiao, Hang Dong, Si Qin, Victor Rühle, Chetan Bansal, Eli Cortez, Íñigo Goiri, Saravan Rajmohan, Qingwei Lin, Dongmei Zhang

CoRR, 2024

Toximatics: Towards Understanding Toxicity in Real-Life Social Situations.

Mayukh Das, Wolf-Tilo Balke

Proceedings of the 25th Annual Meeting of the Special Interest Group on Discourse and Dialogue, 2024

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

Proceedings of the 21st USENIX Symposium on Networked Systems Design and Implementation, 2024

SmartOClock: Workload- and Risk-Aware Overclocking in the Cloud.

Jovan Stojkovic, Pulkit A. 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

Proceedings of the 51st ACM/IEEE Annual International Symposium on Computer Architecture, 2024

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, Dongmei Zhang, Qi Zhang

Proceedings of the 33rd ACM International Conference on Information and Knowledge Management, 2024

2023

Automated Spot Counting in Microbiology.

Chun Pang Lin, Yajie Duan, Davit Sargsyan, Javier Cabrera, Christine M. Livingston, Robert Vogel, John Hartman, Mayukh Das, Willem Talloen, Helena Geys, Evangelos D. Kanoulas, Surya Mohanty

IEEE ACM Trans. Comput. Biol. Bioinform., 2023

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

Proceedings of the IEEE International Conference on Big Data, 2023

2022

Tree DNN: A Deep Container Network.

Brijraj Singh, Swati Gupta, Mayukh Das, Praveen Doreswamy Naidu, Sharan Kumar Allur

CoRR, 2022

Human-guided Collaborative Problem Solving: A Natural Language based Framework.

Harsha Kokel, Mayukh Das, Md. Rakibul Islam, Julia Bonn, Jon Z. Cai, Soham Dan, Anjali Narayan-Chen, Prashant Jayannavar, Janardhan Rao Doppa, Julia Hockenmaier, Sriraam Natarajan, Martha Palmer, Dan Roth

CoRR, 2022

Design and Develop Hardware Aware DNN for Faster Inference.

S. Rajarajeswari, Annapurna P. Patil, Aditya Madhyastha, Akshat Jaitly, Himangshu Shekhar Jha, Sahil Rajesh Bhave, Mayukh Das, N. S. Pradeep

Proceedings of the Intelligent Systems and Applications, 2022

ANNExR: Efficient Anytime Inference in DNNs via Adaptive Intermediate Decision Points.

Annapurna P. Patil, Rajarajeswari Subramanian, Varun Cornelio, S. Venkatesh, M. Varun, K. Shavin, Mayukh Das, N. S. Pradeep

Proceedings of the Intelligent Systems and Applications, 2022

AutoCoMet: Smart Neural Architecture Search via Co-Regulated Shaping Reinforcement.

Mayukh Das, Brijraj Singh, Harsh Kanti Chheda, Pawan Sharma, Pradeep NS

Proceedings of the 26th International Conference on Pattern Recognition, 2022

Quantifying Bias from Decoding Techniques in Natural Language Generation.

Mayukh Das, Wolf-Tilo Balke

Proceedings of the 29th International Conference on Computational Linguistics, 2022

2021

NL-Augmenter: A Framework for Task-Sensitive Natural Language Augmentation.

Kaustubh D. Dhole, Varun Gangal, Sebastian Gehrmann, Aadesh Gupta, Zhenhao Li, Saad Mahamood, Abinaya Mahendiran, Simon Mille, Ashish Srivastava, Samson Tan, Tongshuang Wu, Jascha Sohl-Dickstein, Jinho D. Choi, Eduard H. Hovy, Ondrej Dusek, Sebastian Ruder, Sajant Anand, Nagender Aneja, Rabin Banjade, Lisa Barthe, Hanna Behnke, Ian Berlot-Attwell, Connor Boyle, Caroline Brun, Marco Antonio Sobrevilla Cabezudo, Samuel Cahyawijaya, Emile Chapuis, Wanxiang Che, Mukund Choudhary, Christian Clauss, Pierre Colombo, Filip Cornell, Gautier Dagan, Mayukh Das, Tanay Dixit, Thomas Dopierre, Paul-Alexis Dray, Suchitra Dubey, Tatiana Ekeinhor, Marco Di Giovanni, Tanya Goyal, Rishabh Gupta, Louanes Hamla, Sang Han, Fabrice Harel-Canada, Antoine Honore, Ishan Jindal, Przemyslaw K. Joniak, Denis Kleyko, Venelin Kovatchev, Kalpesh Krishna, Ashutosh Kumar, Stefan Langer, Seungjae Ryan Lee, Corey James Levinson, Hualou Liang, Kaizhao Liang, Zhexiong Liu, Andrey Lukyanenko, Vukosi Marivate, Gerard de Melo, Simon Meoni, Maxime Meyer, Afnan Mir, Nafise Sadat Moosavi, Niklas Muennighoff, Timothy Sum Hon Mun, Kenton Murray, Marcin Namysl, Maria Obedkova, Priti Oli, Nivranshu Pasricha, Jan Pfister, Richard Plant, Vinay Prabhu, Vasile Pais, Libo Qin, Shahab Raji, Pawan Kumar Rajpoot, Vikas Raunak, Roy Rinberg, Nicholas Roberts, Juan Diego Rodriguez, Claude Roux, Paulo Henrique Santos Vasconcellos, Ananya B. Sai, Robin M. Schmidt, Thomas Scialom, Tshephisho Sefara, Saqib Shamsi, Xudong Shen, Yiwen Shi, Haoyue Shi, Anna Shvets, Nick Siegel, Damien Sileo, Jamie Simon, Chandan Singh, Roman Sitelew, Priyank Soni, Taylor Sorensen, William Soto, Aman Srivastava, K. V. Aditya Srivatsa, Tony Sun, Mukund Varma T., A. Tabassum, Fiona Anting Tan, Ryan Teehan, Mo Tiwari, Marie Tolkiehn, Athena Wang, Zijian Wang, Zijie J. Wang, Gloria Wang, Fuxuan Wei, Bryan Wilie, Genta Indra Winata, Xinyi Wu, Witold Wydmanski, Tianbao Xie, Usama Yaseen, Michael A. Yee, Jing Zhang, Yue Zhang

CoRR, 2021

Beyond Simple Images: Human Knowledge-Guided GANs for Clinical Data Generation.

Devendra Singh Dhami, Mayukh Das, Sriraam Natarajan

Proceedings of the 18th International Conference on Principles of Knowledge Representation and Reasoning, 2021

A Framework for Asymmetrical DNN Modularization for Optimal Loading.

Brijraj Singh, Yash Jain, Mayukh Das, Praveen Doreswamy Naidu

Proceedings of the International Joint Conference on Neural Networks, 2021

Human-Guided Learning of Column Networks: Knowledge Injection for Relational Deep Learning.

Mayukh Das, Devendra Singh Dhami, Yang Yu, Gautam Kunapuli, Sriraam Natarajan

Proceedings of the CODS-COMAD 2021: 8th ACM IKDD CODS and 26th COMAD, 2021

2020

Few-Shot Induction of Generalized Logical Concepts via Human Guidance.

Mayukh Das, Nandini Ramanan, Janardhan Rao Doppa, Sriraam Natarajan

Frontiers Robotics AI, 2020

Discriminative Non-Parametric Learning of Arithmetic Circuits.

Nandini Ramanan, Mayukh Das, Kristian Kersting, Sriraam Natarajan

Proceedings of the International Conference on Probabilistic Graphical Models, 2020

Knowledge Intensive Learning of Generative Adversarial Networks.

Devendra Singh Dhami, Mayukh Das, Sriraam Natarajan

Proceedings of the ACM SIGKDD Workshop on Knowledge-infused Mining and Learning for Social Impact co-located with 26th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (Virtual) (SIGKDD 2020), 2020

2019

Planning with actively eliciting preferences.

Mayukh Das, Phillip Odom, Md. Rakibul Islam, Janardhan Rao Doppa, Dan Roth, Sriraam Natarajan

Knowl. Based Syst., 2019

One-Shot Induction of Generalized Logical Concepts via Human Guidance.

Mayukh Das, Nandini Ramanan, Janardhan Rao Doppa, Sriraam Natarajan

CoRR, 2019

Knowledge-augmented Column Networks: Guiding Deep Learning with Advice.

Mayukh Das, Devendra Singh Dhami, Yang Yu, Gautam Kunapuli, Sriraam Natarajan

CoRR, 2019

Human-Guided Learning of Column Networks: Augmenting Deep Learning with Advice.

Mayukh Das, Yang Yu, Devendra Singh Dhami, Gautam Kunapuli, Sriraam Natarajan

CoRR, 2019

Fast Relational Probabilistic Inference and Learning: Approximate Counting via Hypergraphs.

Mayukh Das, Devendra Singh Dhami, Gautam Kunapuli, Kristian Kersting, Sriraam Natarajan

Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence, 2019

2018

Preference-Guided Planning: An Active Elicitation Approach.

Mayukh Das, Phillip Odom, Md. Rakibul Islam, Janardhan Rao Doppa, Dan Roth, Sriraam Natarajan

Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems, 2018

2017

User Friendly Automatic Construction of Background Knowledge: Mode Construction from ER Diagrams.

Alexander L. Hayes, Mayukh Das, Phillip Odom, Sriraam Natarajan

Proceedings of the Knowledge Capture Conference, 2017

Towards Problem Solving Agents that Communicate and Learn.

Anjali Narayan-Chen, Colin Graber, Mayukh Das, Md. Rakibul Islam, Soham Dan, Sriraam Natarajan, Janardhan Rao Doppa, Julia Hockenmaier, Martha Palmer, Dan Roth

Proceedings of the First Workshop on Language Grounding for Robotics, 2017

Active Preference Elicitation for Planning.

Mayukh Das, Md. Rakibul Islam, Janardhan Rao Doppa, Dan Roth, Sriraam Natarajan

Proceedings of the Workshops of the The Thirty-First AAAI Conference on Artificial Intelligence, 2017

2016

Scaling Lifted Probabilistic Inference and Learning Via Graph Databases.

Mayukh Das, Yuqing Wu, Tushar Khot, Kristian Kersting, Sriraam Natarajan

Proceedings of the 2016 SIAM International Conference on Data Mining, 2016