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2020 – today
- 2024
[c17]Pranavi Pathakota, Hardik Meisheri, Harshad Khadilkar:
DCT: Dual Channel Training of Action Embeddings for Reinforcement Learning with Large Discrete Action Spaces. AAMAS 2024: 2411-2413- [c16]Omkar Shelke
, Pranavi Pathakota, Anandsingh Chauhan, Hardik Meisheri, Harshad Khadilkar, Balaraman Ravindran:
A Learning Approach for Discovering Cost-Efficient Integrated Sourcing and Routing Strategies in E-Commerce. COMAD/CODS 2024: 430-438 - 2023
- [c15]Durgesh Kalwar, Omkar Shelke, Somjit Nath, Hardik Meisheri, Harshad Khadilkar:
Follow your Nose: Using General Value Functions for Directed Exploration in Reinforcement Learning. AAMAS 2023: 802-809 - [c14]Harshad Khadilkar, Hardik Meisheri:
Using Contrastive Samples for Identifying and Leveraging Possible Causal Relationships in Reinforcement Learning. COMAD/CODS 2023: 108-112 - [c13]Pranavi Pathakota, Kunwar Zaid, Anulekha Dhara, Hardik Meisheri, Shaun D'Souza, Dheeraj Shah, Harshad Khadilkar:
Learning to Minimize Cost to Serve for Multi-Node Multi-Product Order Fulfilment in Electronic Commerce. COMAD/CODS 2023: 176-184 - [i14]Pranavi Pathakota, Hardik Meisheri, Harshad Khadilkar:
DCT: Dual Channel Training of Action Embeddings for Reinforcement Learning with Large Discrete Action Spaces. CoRR abs/2306.15913 (2023) - [i13]Omkar Shelke, Pranavi Pathakota, Anandsingh Chauhan, Harshad Khadilkar, Hardik Meisheri, Balaraman Ravindran:
Multi-Agent Learning of Efficient Fulfilment and Routing Strategies in E-Commerce. CoRR abs/2311.16171 (2023) - 2022
- [j2]Hardik Meisheri, Nazneen N. Sultana, Mayank Baranwal, Vinita Baniwal, Somjit Nath, Satyam Verma, Balaraman Ravindran, Harshad Khadilkar:
Scalable multi-product inventory control with lead time constraints using reinforcement learning. Neural Comput. Appl. 34(3): 1735-1757 (2022) - [c12]Omkar Shelke, Hardik Meisheri, Harshad Khadilkar:
Identifying efficient curricula for reinforcement learning in complex environments with a fixed computational budget. COMAD/CODS 2022: 81-89 - [i12]Somjit Nath, Omkar Shelke, Durgesh Kalwar, Hardik Meisheri, Harshad Khadilkar:
Follow your Nose: Using General Value Functions for Directed Exploration in Reinforcement Learning. CoRR abs/2203.00874 (2022) - [i11]Hardik Meisheri, Somjit Nath, Mayank Baranwal, Harshad Khadilkar:
A Learning Based Framework for Handling Uncertain Lead Times in Multi-Product Inventory Management. CoRR abs/2203.00885 (2022) - [i10]Harshad Khadilkar, Hardik Meisheri:
Using Contrastive Samples for Identifying and Leveraging Possible Causal Relationships in Reinforcement Learning. CoRR abs/2210.17296 (2022) - 2021
- [c11]Hardik Meisheri, Harshad Khadilkar:
FoLaR: Foggy Latent Representations for Reinforcement Learning with Partial Observability. IJCNN 2021: 1-8 - [i9]Omkar Shelke, Hardik Meisheri, Harshad Khadilkar:
School of hard knocks: Curriculum analysis for Pommerman with a fixed computational budget. CoRR abs/2102.11762 (2021) - [i8]Pranavi Pathakota, Kunwar Zaid, Anulekha Dhara, Hardik Meisheri, Shaun D'Souza, Dheeraj Shah, Harshad Khadilkar:
Learning to Minimize Cost-to-Serve for Multi-Node Multi-Product Order Fulfilment in Electronic Commerce. CoRR abs/2112.08736 (2021) - 2020
- [i7]Nazneen N. Sultana, Hardik Meisheri, Vinita Baniwal, Somjit Nath, Balaraman Ravindran, Harshad Khadilkar:
Reinforcement Learning for Multi-Product Multi-Node Inventory Management in Supply Chains. CoRR abs/2006.04037 (2020) - [i6]Hardik Meisheri, Harshad Khadilkar:
Sample Efficient Training in Multi-Agent Adversarial Games with Limited Teammate Communication. CoRR abs/2011.00424 (2020)
2010 – 2019
- 2019
- [c10]Souvik Barat, Harshad Khadilkar, Hardik Meisheri, Vinay Kulkarni, Vinita Baniwal, Prashant Kumar, Monika Gajrani:
Actor Based Simulation for Closed Loop Control of Supply Chain using Reinforcement Learning. AAMAS 2019: 1802-1804 - [c9]Souvik Barat, Prashant Kumar, Monika Gajrani, Harshad Khadilkar, Hardik Meisheri, Vinita Baniwal, Vinay Kulkarni:
Reinforcement Learning of Supply Chain Control Policy Using Closed Loop Multi-agent Simulation. MABS 2019: 26-38 - [i5]Hardik Meisheri, Vinita Baniwal, Nazneen N. Sultana, Balaraman Ravindran, Harshad Khadilkar:
Reinforcement Learning for Multi-Objective Optimization of Online Decisions in High-Dimensional Systems. CoRR abs/1910.00211 (2019) - [i4]Sachin Thukral, Arnab Chatterjee, Hardik Meisheri, Tushar Kataria, Aman Agarwal, Ishan Verma, Lipika Dey:
Characterizing behavioral trends in a community driven discussion platform. CoRR abs/1911.02771 (2019) - [i3]Hardik Meisheri, Omkar Shelke, Richa Verma, Harshad Khadilkar:
Accelerating Training in Pommerman with Imitation and Reinforcement Learning. CoRR abs/1911.04947 (2019) - 2018
- [c8]Sachin Thukral, Hardik Meisheri, Tushar Kataria, Aman Agarwal, Ishan Verma, Arnab Chatterjee, Lipika Dey:
Analyzing Behavioral Trends in Community Driven Discussion Platforms Like Reddit. ASONAM 2018: 662-669 - [c7]Hardik Meisheri, Lipika Dey:
TCS Research at SemEval-2018 Task 1: Learning Robust Representations using Multi-Attention Architecture. SemEval@NAACL-HLT 2018: 291-299 - [c6]Hardik Meisheri, Harshad Khadilkar:
Learning representations for sentiment classification using Multi-task framework. WASSA@EMNLP 2018: 299-308 - [c5]Ishan Verma, Rahul Ahuja, Hardik Meisheri, Lipika Dey:
Air Pollutant Severity Prediction Using Bi-Directional LSTM Network. WI 2018: 651-654 - [c4]Kaustubh Mani, Ishan Verma, Hardik Meisheri, Lipika Dey:
Multi-Document Summarization Using Distributed Bag-of-Words Model. WI 2018: 672-675 - [i2]Hardik Meisheri, Nagraj Ramrao, Suman Mitra:
Multiclass Common Spatial Pattern for EEG based Brain Computer Interface with Adaptive Learning Classifier. CoRR abs/1802.09046 (2018) - [i1]Sachin Thukral, Hardik Meisheri, Tushar Kataria, Aman Agarwal, Ishan Verma, Arnab Chatterjee, Lipika Dey:
Analyzing behavioral trends in community driven discussion platforms like Reddit. CoRR abs/1809.07087 (2018) - 2017
- [j1]Lipika Dey, Hardik Meisheri, Ishan Verma:
Predictive Analytics with Structured and Unstructured data - a Deep Learning based Approach. IEEE Intell. Informatics Bull. 18(2): 27-34 (2017) - [c3]Hardik Meisheri, Kunal Ranjan, Lipika Dey:
Sentiment Extraction from Consumer-Generated Noisy Short Texts. ICDM Workshops 2017: 399-406 - [c2]Hardik Meisheri, Rupsa Saha, Priyanka Sinha, Lipika Dey:
Textmining at EmoInt-2017: A Deep Learning Approach to Sentiment Intensity Scoring of English Tweets. WASSA@EMNLP 2017: 193-199 - [c1]Ishan Verma, Lipika Dey, Hardik Meisheri:
Detecting, quantifying and accessing impact of news events on Indian stock indices. WI 2017: 550-557
Coauthor Index
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