Mayukh Das

Orcid: 0000-0002-1254-7543

According to our database1, Mayukh Das authored at least 28 papers between 2016 and 2024.

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Bibliography

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

OPPerTune: Post-Deployment Configuration Tuning of Services Made Easy.
Proceedings of the 21st USENIX Symposium on Networked Systems Design and Implementation, 2024

2023
Automated Spot Counting in Microbiology.
IEEE ACM Trans. Comput. Biol. Bioinform., 2023

NASEREX: Optimizing Early Exits via AutoML for Scalable Efficient Inference in Big Image Streams.
Proceedings of the IEEE International Conference on Big Data, 2023

2022
Tree DNN: A Deep Container Network.
CoRR, 2022

Human-guided Collaborative Problem Solving: A Natural Language based Framework.
CoRR, 2022

Design and Develop Hardware Aware DNN for Faster Inference.
Proceedings of the Intelligent Systems and Applications, 2022

ANNExR: Efficient Anytime Inference in DNNs via Adaptive Intermediate Decision Points.
Proceedings of the Intelligent Systems and Applications, 2022

AutoCoMet: Smart Neural Architecture Search via Co-Regulated Shaping Reinforcement.
Proceedings of the 26th International Conference on Pattern Recognition, 2022

Quantifying Bias from Decoding Techniques in Natural Language Generation.
Proceedings of the 29th International Conference on Computational Linguistics, 2022

2021
NL-Augmenter: A Framework for Task-Sensitive Natural Language Augmentation.
CoRR, 2021

Beyond Simple Images: Human Knowledge-Guided GANs for Clinical Data Generation.
Proceedings of the 18th International Conference on Principles of Knowledge Representation and Reasoning, 2021

A Framework for Asymmetrical DNN Modularization for Optimal Loading.
Proceedings of the International Joint Conference on Neural Networks, 2021

Human-Guided Learning of Column Networks: Knowledge Injection for Relational Deep Learning.
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.
Frontiers Robotics AI, 2020

Discriminative Non-Parametric Learning of Arithmetic Circuits.
Proceedings of the International Conference on Probabilistic Graphical Models, 2020

Knowledge Intensive Learning of Generative Adversarial Networks.
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.
Knowl. Based Syst., 2019

One-Shot Induction of Generalized Logical Concepts via Human Guidance.
CoRR, 2019

Knowledge-augmented Column Networks: Guiding Deep Learning with Advice.
CoRR, 2019

Human-Guided Learning of Column Networks: Augmenting Deep Learning with Advice.
CoRR, 2019

Fast Relational Probabilistic Inference and Learning: Approximate Counting via Hypergraphs.
Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence, 2019

2018
Preference-Guided Planning: An Active Elicitation Approach.
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.
Proceedings of the Knowledge Capture Conference, 2017

Towards Problem Solving Agents that Communicate and Learn.
Proceedings of the First Workshop on Language Grounding for Robotics, 2017

Active Preference Elicitation for Planning.
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.
Proceedings of the 2016 SIAM International Conference on Data Mining, 2016


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