Chandrashekar Lakshminarayanan

According to our database, Chandrashekar Lakshminarayanan authored at least 26 papers between 2014 and 2025.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2025

Interpreting Adversarial Attacks and Defences using Architectures with Enhanced Interpretability.

Akshay G. Rao, Chandra Shekar Lakshminarayanan, Arun Rajkumar

CoRR, February, 2025

Approximate linear programming for decentralized policy iteration in cooperative multi-agent Markov decision processes.

Lakshmi Mandal, Chandrashekar Lakshminarayanan, Shalabh Bhatnagar

Syst. Control. Lett., 2025

Deep Networks Learn Features From Local Discontinuities in the Label Function.

Prithaj Banerjee, Harish Guruprasad Ramaswamy, Mahesh Lorik Yadav, Chandra Shekar Lakshminarayanan

Proceedings of the Thirteenth International Conference on Learning Representations, 2025

2024

Transformers with Sparse Attention for Granger Causality.

Riya Mahesh, Rahul Vashisht, Chandrashekar Lakshminarayanan

CoRR, 2024

Half-Space Feature Learning in Neural Networks.

Mahesh Lorik Yadav, Harish Guruprasad Ramaswamy, Chandrashekar Lakshminarayanan

CoRR, 2024

Deployability of Deep Reinforcement Learning in Portfolio Management.

Ishwar Govind, Jerry Thomas, Chandrashekar Lakshminarayanan

Proceedings of the 8th International Conference on Data Science and Management of Data (12th ACM IKDD CODS and 30th COMAD), 2024

2023

Approximate Linear Programming and Decentralized Policy Improvement in Cooperative Multi-agent Markov Decision Processes.

Lakshmi Mandal, Chandrashekar Lakshminarayanan, Shalabh Bhatnagar

CoRR, 2023

Unsupervised Concept Tagging of Mathematical Questions from Student Explanations.

K. M. Shabana, Chandrashekar Lakshminarayanan

Proceedings of the Artificial Intelligence in Education - 24th International Conference, 2023

2022

Explicitising The Implicit Intrepretability of Deep Neural Networks Via Duality.

Chandrashekar Lakshminarayanan, Amit Vikram Singh, Arun Rajkumar

CoRR, 2022

CurriculumTutor: An Adaptive Algorithm for Mastering a Curriculum.

K. M. Shabana, Chandrashekar Lakshminarayanan, Jude K. Anil

Proceedings of the Artificial Intelligence in Education - 23rd International Conference, 2022

2021

Disentangling deep neural networks with rectified linear units using duality.

Chandrashekar Lakshminarayanan, Amit Vikram Singh

CoRR, 2021

2020

Deep Gated Networks: A framework to understand training and generalisation in deep learning.

Chandrashekar Lakshminarayanan, Amit Vikram Singh

CoRR, 2020

Neural Path Features and Neural Path Kernel : Understanding the role of gates in deep learning.

Chandrashekar Lakshminarayanan, Amit Vikram Singh

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

2019

DeepAir: Air Quality Prediction using Deep Neural Network.

Pratyush Singh, T. Lakshmi Narasimhan, Chandra Shekar Lakshminarayanan

Proceedings of the TENCON 2019, 2019

2018

A Linearly Relaxed Approximate Linear Program for Markov Decision Processes.

Chandrashekar Lakshminarayanan, Shalabh Bhatnagar, Csaba Szepesvári

IEEE Trans. Autom. Control., 2018

Linear Stochastic Approximation: How Far Does Constant Step-Size and Iterate Averaging Go?

Chandrashekar Lakshminarayanan, Csaba Szepesvári

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2018

2017

Linear Stochastic Approximation: Constant Step-Size and Iterate Averaging.

Chandrashekar Lakshminarayanan, Csaba Szepesvári

CoRR, 2017

A stability criterion for two timescale stochastic approximation schemes.

Chandrashekar Lakshminarayanan, Shalabh Bhatnagar

Autom., 2017

Scalable Performance Tuning of Hadoop MapReduce: A Noisy Gradient Approach.

Sandeep Kumar, Sindhu Padakandla, Chandrashekar Lakshminarayanan, Priyank Parihar, K. Gopinath, Shalabh Bhatnagar

Proceedings of the 2017 IEEE 10th International Conference on Cloud Computing (CLOUD), 2017

2016

Performance Tuning of Hadoop MapReduce: A Noisy Gradient Approach.

Sandeep Kumar, Sindhu Padakandla, Chandrashekar Lakshminarayanan, Priyank Parihar, K. Gopinath, Shalabh Bhatnagar

CoRR, 2016

Shaping Proto-Value Functions Using Rewards.

Raj Kumar Maity, Chandrashekar Lakshminarayanan, Sindhu Padakandla, Shalabh Bhatnagar

Proceedings of the ECAI 2016 - 22nd European Conference on Artificial Intelligence, 29 August-2 September 2016, The Hague, The Netherlands, 2016

2015

Shaping Proto-Value Functions via Rewards.

Chandrashekar Lakshmi Narayanan, Raj Kumar Maity, Shalabh Bhatnagar

CoRR, 2015

A Generalized Reduced Linear Program for Markov Decision Processes.

Chandrashekar Lakshminarayanan, Shalabh Bhatnagar

Proceedings of the Twenty-Ninth AAAI Conference on Artificial Intelligence, 2015

2014

Approximate Dynamic Programming based on Projection onto the (min, +) subsemimodule.

Chandrashekar Lakshminarayanan, Shalabh Bhatnagar

CoRR, 2014

A Markov Decision Process Framework for Predictable Job Completion Times on Crowdsourcing Platforms.

Chandrashekar Lakshminarayanan, Ayush Dubey, Shalabh Bhatnagar, Chithralekha Balamurugan

Proceedings of the Second AAAI Conference on Human Computation and Crowdsourcing, 2014

Approximate Dynamic Programming with (min; +) linear function approximation for Markov decision processes.

Chandrashekar Lakshminarayanan, Shalabh Bhatnagar

Proceedings of the 53rd IEEE Conference on Decision and Control, 2014