A stability criterion for two timescale stochastic approximation schemes von Lakshminarayanan, Chandrashekar, Bhatnagar, Shalabh

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A Linearly Relaxed Approximate Linear Program for Markov Decision Processes von Lakshminarayanan, Chandrashekar, Bhatnagar, Shalabh, Szepesvari, Csaba

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Unsupervised Concept Tagging of Mathematical Questions from Student Explanations von Shabana, K. M., Lakshminarayanan, Chandrashekar

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CurriculumTutor: An Adaptive Algorithm for Mastering a Curriculum von Shabana, K. M., Lakshminarayanan, Chandrashekar, Anil, Jude K.

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Transformers with Sparse Attention for Granger Causality von Mahesh, Riya, Vashisht, Rahul, Lakshminarayanan, Chandrashekar

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Approximate Linear Programming for Decentralized Policy Iteration in Cooperative Multi-agent Markov Decision Processes von Mandal, Lakshmi, Lakshminarayanan, Chandrashekar, Bhatnagar, Shalabh

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Disentangling deep neural networks with rectified linear units using duality von Lakshminarayanan, Chandrashekar, Singh, Amit Vikram

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Half-Space Feature Learning in Neural Networks von Yadav, Mahesh Lorik, Ramaswamy, Harish Guruprasad, Lakshminarayanan, Chandrashekar

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Explicitising The Implicit Intrepretability of Deep Neural Networks Via Duality von Lakshminarayanan, Chandrashekar, Singh, Amit Vikram, Rajkumar, Arun

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Neural Path Features and Neural Path Kernel : Understanding the role of gates in deep learning von Lakshminarayanan, Chandrashekar, Singh, Amit Vikram

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Deep Gated Networks: A framework to understand training and generalisation in deep learning von Lakshminarayanan, Chandrashekar, Singh, Amit Vikram

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Transformers with Sparse Attention for Granger Causality von Riya Mahesh, Vashisht, Rahul, Lakshminarayanan, Chandrashekar

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Linear Stochastic Approximation: Constant Step-Size and Iterate Averaging von Lakshminarayanan, Chandrashekar, Szepesvári, Csaba

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Approximate Linear Programming for Decentralized Policy Iteration in Cooperative Multi-agent Markov Decision Processes von Mandal, Lakshmi, Lakshminarayanan, Chandrashekar, Bhatnagar, Shalabh

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Disentangling deep neural networks with rectified linear units using duality von Lakshminarayanan, Chandrashekar, Amit Vikram Singh

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Neural Path Features and Neural Path Kernel : Understanding the role of gates in deep learning von Lakshminarayanan, Chandrashekar, Amit Vikram Singh

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Half-Space Feature Learning in Neural Networks von Yadav, Mahesh Lorik, Harish Guruprasad Ramaswamy, Lakshminarayanan, Chandrashekar

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System, method, and computer program product for connecting power supplies in a mixed signal design von Chetput, Chandrashekar Lakshminarayanan, Zhang, Nan

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Explicitising The Implicit Intrepretability of Deep Neural Networks Via Duality von Lakshminarayanan, Chandrashekar, Amit Vikram Singh, Rajkumar, Arun

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A Generalized Reduced Linear Program for Markov Decision Processes von Lakshminarayanan, Chandrashekar, Bhatnagar, Shalabh

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