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ORCIDMayukh Das
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2020 – today
- 2024
[c20]Lu Wang, Mayukh Das, Fangkai Yang, Chao Du, Bo Qiao, Hang Dong, Chetan Bansal, Si Qin, Saravan Rajmohan, Qingwei Lin, Dongmei Zhang, Qi Zhang:
COIN: Chance-Constrained Imitation Learning for Safe and Adaptive Resource Oversubscription under Uncertainty. CIKM 2024: 4939-4947- [c19]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:
SmartOClock: Workload- and Risk-Aware Overclocking in the Cloud. ISCA 2024: 437-451 - [c18]Gagan Somashekar, Karan Tandon, Anush Kini, Chieh-Chun Chang, Petr Husak, Ranjita Bhagwan, Mayukh Das, Anshul Gandhi, Nagarajan Natarajan:
OPPerTune: Post-Deployment Configuration Tuning of Services Made Easy. NSDI 2024 - [c17]Mayukh Das, Wolf-Tilo Balke:
Toximatics: Towards Understanding Toxicity in Real-Life Social Situations. SIGDIAL 2024: 770-785 - [i11]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:
Risk-aware Adaptive Virtual CPU Oversubscription in Microsoft Cloud via Prototypical Human-in-the-loop Imitation Learning. CoRR abs/2401.07033 (2024) - [i10]Lu Wang, Mayukh Das, Fangkai Yang, Chao Du, Bo Qiao, Hang Dong, Si Qin, Chetan Bansal, Qingwei Lin, Saravan Rajmohan, Dongmei Zhang, Qi Zhang:
COIN: Chance-Constrained Imitation Learning for Uncertainty-aware Adaptive Resource Oversubscription Policy. CoRR abs/2401.07051 (2024) - 2023
- [j3]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:
Automated Spot Counting in Microbiology. IEEE ACM Trans. Comput. Biol. Bioinform. 20(6): 3703-3714 (2023) - [c16]Aakash Kapoor, Rajath Elias Soans, Soham Dixit, Pradeep NS, Brijraj Singh, Mayukh Das:
NASEREX: Optimizing Early Exits via AutoML for Scalable Efficient Inference in Big Image Streams. IEEE Big Data 2023: 5266-5271 - 2022
- [c15]Mayukh Das, Wolf-Tilo Balke:
Quantifying Bias from Decoding Techniques in Natural Language Generation. COLING 2022: 1311-1323 - [c14]Mayukh Das, Brijraj Singh, Harsh Kanti Chheda, Pawan Sharma, Pradeep NS:
AutoCoMet: Smart Neural Architecture Search via Co-Regulated Shaping Reinforcement. ICPR 2022: 2568-2574 - [c13]Annapurna P. Patil, Rajarajeswari Subramanian, Varun Cornelio, S. Venkatesh, M. Varun, K. Shavin, Mayukh Das, N. S. Pradeep:
ANNExR: Efficient Anytime Inference in DNNs via Adaptive Intermediate Decision Points. IntelliSys (2) 2022: 1-25 - [c12]S. Rajarajeswari, Annapurna P. Patil, Aditya Madhyastha, Akshat Jaitly, Himangshu Shekhar Jha, Sahil Rajesh Bhave, Mayukh Das, N. S. Pradeep:
Design and Develop Hardware Aware DNN for Faster Inference. IntelliSys (3) 2022: 309-318 - [i9]Mayukh Das, Brijraj Singh, Harsh Kanti Chheda, Pawan Sharma, Pradeep NS:
AutoCoMet: Smart Neural Architecture Search via Co-Regulated Shaping Reinforcement. CoRR abs/2203.15408 (2022) - [i8]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:
Human-guided Collaborative Problem Solving: A Natural Language based Framework. CoRR abs/2207.09566 (2022) - [i7]Brijraj Singh, Swati Gupta, Mayukh Das, Praveen Doreswamy Naidu, Sharan Kumar Allur:
Tree DNN: A Deep Container Network. CoRR abs/2212.03474 (2022) - 2021
- [c11]Mayukh Das, Devendra Singh Dhami, Yang Yu, Gautam Kunapuli, Sriraam Natarajan:
Human-Guided Learning of Column Networks: Knowledge Injection for Relational Deep Learning. COMAD/CODS 2021: 110-118 - [c10]Brijraj Singh, Yash Jain, Mayukh Das, Praveen Doreswamy Naidu:
A Framework for Asymmetrical DNN Modularization for Optimal Loading. IJCNN 2021: 1-8 - [c9]Devendra Singh Dhami, Mayukh Das, Sriraam Natarajan:
Beyond Simple Images: Human Knowledge-Guided GANs for Clinical Data Generation. KR 2021: 247-257 - [i6]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:
NL-Augmenter: A Framework for Task-Sensitive Natural Language Augmentation. CoRR abs/2112.02721 (2021) - 2020
- [j2]Mayukh Das, Nandini Ramanan, Janardhan Rao Doppa, Sriraam Natarajan:
Few-Shot Induction of Generalized Logical Concepts via Human Guidance. Frontiers Robotics AI 7: 122 (2020) - [c8]Devendra Singh Dhami, Mayukh Das, Sriraam Natarajan:
Knowledge Intensive Learning of Generative Adversarial Networks. KiML@KDD 2020: 10-16 - [c7]Nandini Ramanan, Mayukh Das, Kristian Kersting, Sriraam Natarajan:
Discriminative Non-Parametric Learning of Arithmetic Circuits. PGM 2020: 353-364
2010 – 2019
- 2019
- [j1]Mayukh Das, Phillip Odom, Md. Rakibul Islam, Janardhan Rao Doppa, Dan Roth, Sriraam Natarajan:
Planning with actively eliciting preferences. Knowl. Based Syst. 165: 219-227 (2019) - [c6]Mayukh Das, Devendra Singh Dhami, Gautam Kunapuli, Kristian Kersting, Sriraam Natarajan:
Fast Relational Probabilistic Inference and Learning: Approximate Counting via Hypergraphs. AAAI 2019: 7816-7824 - [i5]Mayukh Das, Yang Yu, Devendra Singh Dhami, Gautam Kunapuli, Sriraam Natarajan:
Human-Guided Learning of Column Networks: Augmenting Deep Learning with Advice. CoRR abs/1904.06950 (2019) - [i4]Mayukh Das, Devendra Singh Dhami, Yang Yu, Gautam Kunapuli, Sriraam Natarajan:
Knowledge-augmented Column Networks: Guiding Deep Learning with Advice. CoRR abs/1906.01432 (2019) - [i3]Mayukh Das, Nandini Ramanan, Janardhan Rao Doppa, Sriraam Natarajan:
One-Shot Induction of Generalized Logical Concepts via Human Guidance. CoRR abs/1912.07060 (2019) - [i2]Alexander L. Hayes, Mayukh Das, Phillip Odom, Sriraam Natarajan:
User Friendly Automatic Construction of Background Knowledge: Mode Construction from ER Diagrams. CoRR abs/1912.07650 (2019) - 2018
- [c5]Mayukh Das, Phillip Odom, Md. Rakibul Islam, Janardhan Rao Doppa, Dan Roth, Sriraam Natarajan:
Preference-Guided Planning: An Active Elicitation Approach. AAMAS 2018: 1921-1923 - [i1]Mayukh Das, Phillip Odom, Md. Rakibul Islam, Janardhan Rao Doppa, Dan Roth, Sriraam Natarajan:
Preference-Guided Planning: An Active Elicitation Approach. CoRR abs/1804.07404 (2018) - 2017
- [c4]Mayukh Das, Md. Rakibul Islam, Janardhan Rao Doppa, Dan Roth, Sriraam Natarajan:
Active Preference Elicitation for Planning. AAAI Workshops 2017 - [c3]Anjali Narayan-Chen, Colin Graber, Mayukh Das, Md. Rakibul Islam, Soham Dan, Sriraam Natarajan, Janardhan Rao Doppa, Julia Hockenmaier, Martha Palmer, Dan Roth:
Towards Problem Solving Agents that Communicate and Learn. RoboNLP@ACL 2017: 95-103 - [c2]Alexander L. Hayes, Mayukh Das, Phillip Odom, Sriraam Natarajan:
User Friendly Automatic Construction of Background Knowledge: Mode Construction from ER Diagrams. K-CAP 2017: 30:1-30:8 - 2016
- [c1]Mayukh Das, Yuqing Wu, Tushar Khot, Kristian Kersting, Sriraam Natarajan:
Scaling Lifted Probabilistic Inference and Learning Via Graph Databases. SDM 2016: 738-746
Coauthor Index
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