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ORCIDChandrashekar Lakshminarayanan
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- affiliation: Indian Institute of Technology Madras, India
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2020 – today
- 2025
[j3]Lakshmi Mandal
, Chandrashekar Lakshminarayanan, Shalabh Bhatnagar:
Approximate linear programming for decentralized policy iteration in cooperative multi-agent Markov decision processes. Syst. Control. Lett. 196: 106003 (2025)- [c12]Prithaj Banerjee, Harish Guruprasad Ramaswamy, Mahesh Lorik Yadav, Chandra Shekar Lakshminarayanan:
Deep Networks Learn Features From Local Discontinuities in the Label Function. ICLR 2025 - [i15]Akshay G. Rao, Chandra Shekar Lakshminarayanan, Arun Rajkumar:
Interpreting Adversarial Attacks and Defences using Architectures with Enhanced Interpretability. CoRR abs/2502.15017 (2025) - 2024
- [c11]Ishwar Govind, Jerry Thomas, Chandrashekar Lakshminarayanan:
Deployability of Deep Reinforcement Learning in Portfolio Management. COMAD/CODS (December) 2024: 61-65 - [i14]Mahesh Lorik Yadav, Harish Guruprasad Ramaswamy, Chandrashekar Lakshminarayanan:
Half-Space Feature Learning in Neural Networks. CoRR abs/2404.04312 (2024) - [i13]Riya Mahesh, Rahul Vashisht, Chandrashekar Lakshminarayanan:
Transformers with Sparse Attention for Granger Causality. CoRR abs/2411.13264 (2024) - 2023
- [c10]K. M. Shabana, Chandrashekar Lakshminarayanan:
Unsupervised Concept Tagging of Mathematical Questions from Student Explanations. AIED 2023: 627-638 - [i12]Lakshmi Mandal, Chandrashekar Lakshminarayanan, Shalabh Bhatnagar:
Approximate Linear Programming and Decentralized Policy Improvement in Cooperative Multi-agent Markov Decision Processes. CoRR abs/2311.11789 (2023) - 2022
- [c9]K. M. Shabana, Chandrashekar Lakshminarayanan, Jude K. Anil:
CurriculumTutor: An Adaptive Algorithm for Mastering a Curriculum. AIED (1) 2022: 319-331 - [i11]Chandrashekar Lakshminarayanan, Amit Vikram Singh, Arun Rajkumar:
Explicitising The Implicit Intrepretability of Deep Neural Networks Via Duality. CoRR abs/2203.16455 (2022) - 2021
- [i10]Chandrashekar Lakshminarayanan, Amit Vikram Singh:
Disentangling deep neural networks with rectified linear units using duality. CoRR abs/2110.03403 (2021) - 2020
- [c8]Chandrashekar Lakshminarayanan, Amit Vikram Singh:
Neural Path Features and Neural Path Kernel : Understanding the role of gates in deep learning. NeurIPS 2020 - [i9]Chandrashekar Lakshminarayanan, Amit Vikram Singh:
Deep Gated Networks: A framework to understand training and generalisation in deep learning. CoRR abs/2002.03996 (2020) - [i8]Chandrashekar Lakshminarayanan, Amit Vikram Singh:
Neural Path Features and Neural Path Kernel : Understanding the role of gates in deep learning. CoRR abs/2006.10529 (2020)
2010 – 2019
- 2019
- [c7]Pratyush Singh, T. Lakshmi Narasimhan, Chandra Shekar Lakshminarayanan:
DeepAir: Air Quality Prediction using Deep Neural Network. TENCON 2019: 869-873 - 2018
- [j2]Chandrashekar Lakshminarayanan, Shalabh Bhatnagar, Csaba Szepesvári:
A Linearly Relaxed Approximate Linear Program for Markov Decision Processes. IEEE Trans. Autom. Control. 63(4): 1185-1191 (2018) - [c6]Chandrashekar Lakshminarayanan, Csaba Szepesvári:
Linear Stochastic Approximation: How Far Does Constant Step-Size and Iterate Averaging Go? AISTATS 2018: 1347-1355 - 2017
- [j1]Chandrashekar Lakshminarayanan, Shalabh Bhatnagar:
A stability criterion for two timescale stochastic approximation schemes. Autom. 79: 108-114 (2017) - [c5]Sandeep Kumar, Sindhu Padakandla, Chandrashekar Lakshminarayanan, Priyank Parihar, K. Gopinath, Shalabh Bhatnagar:
Scalable Performance Tuning of Hadoop MapReduce: A Noisy Gradient Approach. CLOUD 2017: 375-382 - [i7]Chandrashekar Lakshminarayanan, Shalabh Bhatnagar, Csaba Szepesvári:
A Linearly Relaxed Approximate Linear Program for Markov Decision Processes. CoRR abs/1704.02544 (2017) - [i6]Chandrashekar Lakshminarayanan, Csaba Szepesvári:
Linear Stochastic Approximation: Constant Step-Size and Iterate Averaging. CoRR abs/1709.04073 (2017) - 2016
- [c4]Raj Kumar Maity, Chandrashekar Lakshminarayanan, Sindhu Padakandla, Shalabh Bhatnagar:
Shaping Proto-Value Functions Using Rewards. ECAI 2016: 1690-1691 - [i5]Sandeep Kumar, Sindhu Padakandla, Chandrashekar Lakshminarayanan, Priyank Parihar, K. Gopinath, Shalabh Bhatnagar:
Performance Tuning of Hadoop MapReduce: A Noisy Gradient Approach. CoRR abs/1611.10052 (2016) - 2015
- [c3]Chandrashekar Lakshminarayanan, Shalabh Bhatnagar:
A Generalized Reduced Linear Program for Markov Decision Processes. AAAI 2015: 2722-2728 - [i4]Chandrashekar Lakshmi Narayanan, Raj Kumar Maity, Shalabh Bhatnagar:
Shaping Proto-Value Functions via Rewards. CoRR abs/1511.08589 (2015) - 2014
- [c2]Chandrashekar Lakshminarayanan, Shalabh Bhatnagar:
Approximate Dynamic Programming with (min; +) linear function approximation for Markov decision processes. CDC 2014: 1588-1593 - [c1]Chandrashekar Lakshminarayanan, Ayush Dubey, Shalabh Bhatnagar, Chithralekha Balamurugan:
A Markov Decision Process Framework for Predictable Job Completion Times on Crowdsourcing Platforms. HCOMP 2014: 34-35 - [i3]Chandrashekar Lakshminarayanan, Shalabh Bhatnagar:
Approximate Dynamic Programming based on Projection onto the (min, +) subsemimodule. CoRR abs/1403.4175 (2014) - [i2]Chandrashekar Lakshminarayanan, Shalabh Bhatnagar:
Approximate dynamic programming with $(\min, +)$ linear function approximation for Markov decision processes. CoRR abs/1403.4179 (2014) - [i1]Chandrashekar Lakshminarayanan, Shalabh Bhatnagar:
A Generalized Reduced Linear Program for Markov Decision Processes. CoRR abs/1409.3536 (2014)
Coauthor Index
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