Chandrashekar Lakshminarayanan

Publication Activity (10 Years)

Years Active: 2014-2024
Publications (10 Years): 18

Top Topics

Markov Decision Process

Stochastic Approximation

Approximate Dynamic Programming

Top Venues

Publications

Mahesh Lorik Yadav, Harish Guruprasad Ramaswamy, Chandrashekar Lakshminarayanan
Half-Space Feature Learning in Neural Networks. CoRR (2024)
Lakshmi Mandal, Chandrashekar Lakshminarayanan, Shalabh Bhatnagar
Approximate Linear Programming and Decentralized Policy Improvement in Cooperative Multi-agent Markov Decision Processes. CoRR (2023)
K. M. Shabana, Chandrashekar Lakshminarayanan
Unsupervised Concept Tagging of Mathematical Questions from Student Explanations. AIED (2023)
Chandrashekar Lakshminarayanan, Amit Vikram Singh, Arun Rajkumar
Explicitising The Implicit Intrepretability of Deep Neural Networks Via Duality. CoRR (2022)
K. M. Shabana, Chandrashekar Lakshminarayanan, Jude K. Anil
CurriculumTutor: An Adaptive Algorithm for Mastering a Curriculum. AIED (1) (2022)
Chandrashekar Lakshminarayanan, Amit Vikram Singh
Disentangling deep neural networks with rectified linear units using duality. CoRR (2021)
Chandrashekar Lakshminarayanan, Amit Vikram Singh
Neural Path Features and Neural Path Kernel : Understanding the role of gates in deep learning. CoRR (2020)
Chandrashekar Lakshminarayanan, Amit Vikram Singh
Deep Gated Networks: A framework to understand training and generalisation in deep learning. CoRR (2020)
Chandrashekar Lakshminarayanan, Amit Vikram Singh
Neural Path Features and Neural Path Kernel : Understanding the role of gates in deep learning. NeurIPS (2020)
Chandrashekar Lakshminarayanan, Shalabh Bhatnagar, Csaba Szepesvári
A Linearly Relaxed Approximate Linear Program for Markov Decision Processes. IEEE Trans. Autom. Control. 63 (4) (2018)
Chandrashekar Lakshminarayanan, Csaba Szepesvári
Linear Stochastic Approximation: How Far Does Constant Step-Size and Iterate Averaging Go? AISTATS (2018)
Sandeep Kumar, Sindhu Padakandla, Chandrashekar Lakshminarayanan, Priyank Parihar, K. Gopinath, Shalabh Bhatnagar
Scalable Performance Tuning of Hadoop MapReduce: A Noisy Gradient Approach. CLOUD (2017)
Chandrashekar Lakshminarayanan, Shalabh Bhatnagar
A stability criterion for two timescale stochastic approximation schemes. Autom. 79 (2017)
Chandrashekar Lakshminarayanan, Shalabh Bhatnagar, Csaba Szepesvári
A Linearly Relaxed Approximate Linear Program for Markov Decision Processes. CoRR (2017)
Chandrashekar Lakshminarayanan, Csaba Szepesvári
Linear Stochastic Approximation: Constant Step-Size and Iterate Averaging. CoRR (2017)
Sandeep Kumar, Sindhu Padakandla, Chandrashekar Lakshminarayanan, Priyank Parihar, K. Gopinath, Shalabh Bhatnagar
Performance Tuning of Hadoop MapReduce: A Noisy Gradient Approach. CoRR (2016)
Raj Kumar Maity, Chandrashekar Lakshminarayanan, Sindhu Padakandla, Shalabh Bhatnagar
Shaping Proto-Value Functions Using Rewards. ECAI (2016)
Chandrashekar Lakshminarayanan, Shalabh Bhatnagar
A Generalized Reduced Linear Program for Markov Decision Processes. AAAI (2015)
Chandrashekar Lakshminarayanan, Shalabh Bhatnagar
Approximate Dynamic Programming based on Projection onto the (min, +) subsemimodule. CoRR (2014)
Chandrashekar Lakshminarayanan, Shalabh Bhatnagar
Approximate Dynamic Programming with (min; +) linear function approximation for Markov decision processes. CDC (2014)
Chandrashekar Lakshminarayanan, Shalabh Bhatnagar
A Generalized Reduced Linear Program for Markov Decision Processes. CoRR (2014)
Chandrashekar Lakshminarayanan, Ayush Dubey, Shalabh Bhatnagar, Chithralekha Balamurugan
A Markov Decision Process Framework for Predictable Job Completion Times on Crowdsourcing Platforms. HCOMP (2014)
Chandrashekar Lakshminarayanan, Shalabh Bhatnagar
Approximate dynamic programming with $(\min, +)$ linear function approximation for Markov decision processes. CoRR (2014)