22 citations · 65 across the 10 of their papers we have counts for
9 papers · 1 filter
Trust Guided Decision Transformer
Chainesh Gautam, Raghuram Bharadwaj Diddigi, Chandramouli Kamanchi +3
Decision Transformer performance degrades on long rollouts because the conditioning context drifts out of the training distribution. We show that this drift is visible through the…
Towards Unbiased Evaluation of Time-series Anomaly Detector
Debarpan Bhattacharya, Sumanta Mukherjee, Chandramouli Kamanchi +3
Time series anomaly detection (TSAD) is an evolving area of research motivated by its critical applications, such as detecting seismic activity, sensor failures in industrial plant…
Activations Through Extensions: A Framework To Boost Performance Of Neural Networks
Chandramouli Kamanchi, Sumanta Mukherjee, Kameshwaran Sampath +4
Activation functions are non-linearities in neural networks that allow them to learn complex mapping between inputs and outputs. Typical choices for activation functions are ReLU,…
A Convergent Off-Policy Temporal Difference Algorithm
Raghuram Bharadwaj Diddigi, Chandramouli Kamanchi, Shalabh Bhatnagar
Learning the value function of a given policy (target policy) from the data samples obtained from a different policy (behavior policy) is an important problem in Reinforcement Lear…
Generalized Speedy Q-learning
Indu John, Chandramouli Kamanchi, Shalabh Bhatnagar
In this paper, we derive a generalization of the Speedy Q-learning (SQL) algorithm that was proposed in the Reinforcement Learning (RL) literature to handle slow convergence of Wat…
A Generalized Minimax Q-learning Algorithm for Two-Player Zero-Sum Stochastic Games
Raghuram Bharadwaj Diddigi, Chandramouli Kamanchi, Shalabh Bhatnagar
We consider the problem of two-player zero-sum games. This problem is formulated as a min-max Markov game in the literature. The solution of this game, which is the min-max payoff,…
Generalized Second Order Value Iteration in Markov Decision Processes
Chandramouli Kamanchi, Raghuram Bharadwaj Diddigi, Shalabh Bhatnagar
Value iteration is a fixed point iteration technique utilized to obtain the optimal value function and policy in a discounted reward Markov Decision Process (MDP). Here, a contract…
Successive Over Relaxation Q-Learning
Chandramouli Kamanchi, Raghuram Bharadwaj Diddigi, Shalabh Bhatnagar
In a discounted reward Markov Decision Process (MDP), the objective is to find the optimal value function, i.e., the value function corresponding to an optimal policy. This problem…
An Online Sample Based Method for Mode Estimation using ODE Analysis of Stochastic Approximation Algorithms
Chandramouli Kamanchi, Raghuram Bharadwaj Diddigi, Prabuchandran K. J. +1
One of the popular measures of central tendency that provides better representation and interesting insights of the data compared to the other measures like mean and median is the…