39 citations · 79 across the 11 of their papers we have counts for
12 papers
SARC: Soft Actor Retrospective Critic
Sukriti Verma, Ayush Chopra, Jayakumar Subramanian +4
The two-time scale nature of SAC, which is an actor-critic algorithm, is characterised by the fact that the critic estimate has not converged for the actor at any given time, but s…
HyHTM: Hyperbolic Geometry based Hierarchical Topic Models
Simra Shahid, Tanay Anand, Nikitha Srikanth +3
Hierarchical Topic Models (HTMs) are useful for discovering topic hierarchies in a collection of documents. However, traditional HTMs often produce hierarchies where lowerlevel top…
Q-means using variational quantum feature embedding
Arvind S Menon, Nikaash Puri
This paper proposes a hybrid quantum-classical algorithm that learns a suitable quantum feature map that separates unlabelled data that is originally non linearly separable in the…
Status-quo policy gradient in Multi-Agent Reinforcement Learning
Pinkesh Badjatiya, Mausoom Sarkar, Nikaash Puri +4
Individual rationality, which involves maximizing expected individual returns, does not always lead to high-utility individual or group outcomes in multi-agent problems. For instan…
Video2Skill: Adapting Events in Demonstration Videos to Skills in an Environment using Cyclic MDP Homomorphisms
Sumedh A Sontakke, Sumegh Roychowdhury, Mausoom Sarkar +3
Humans excel at learning long-horizon tasks from demonstrations augmented with textual commentary, as evidenced by the burgeoning popularity of tutorial videos online. Intuitively,…
Information-theoretic Evolution of Model Agnostic Global Explanations
Sukriti Verma, Nikaash Puri, Piyush Gupta +1
Explaining the behavior of black box machine learning models through human interpretable rules is an important research area. Recent work has focused on explaining model behavior l…
SHERLock: Self-Supervised Hierarchical Event Representation Learning
Sumegh Roychowdhury, Sumedh A. Sontakke, Nikaash Puri +5
Temporal event representations are an essential aspect of learning among humans. They allow for succinct encoding of the experiences we have through a variety of sensory inputs. Al…
MixBoost: Synthetic Oversampling with Boosted Mixup for Handling Extreme Imbalance
Anubha Kabra, Ayush Chopra, Nikaash Puri +4
Training a classification model on a dataset where the instances of one class outnumber those of the other class is a challenging problem. Such imbalanced datasets are standard in…
Inducing Cooperative behaviour in Sequential-Social dilemmas through Multi-Agent Reinforcement Learning using Status-Quo Loss
Pinkesh Badjatiya, Mausoom Sarkar, Abhishek Sinha +4
In social dilemma situations, individual rationality leads to sub-optimal group outcomes. Several human engagements can be modeled as a sequential (multi-step) social dilemmas. How…
Explain Your Move: Understanding Agent Actions Using Specific and Relevant Feature Attribution
Nikaash Puri, Sukriti Verma, Piyush Gupta +4
As deep reinforcement learning (RL) is applied to more tasks, there is a need to visualize and understand the behavior of learned agents. Saliency maps explain agent behavior by hi…
OpticalGAN : Generative Adversarial Networks for Continuous Variable Quantum Computation
Nilay Shrivastava, Nikaash Puri, Piyush Gupta +2
We present OpticalGAN, an extension of quantum generative adversarial networks for continuous-variable quantum computation. OpticalGAN consists of photonic variational circuits com…
MAGIX: Model Agnostic Globally Interpretable Explanations
Nikaash Puri, Piyush Gupta, Pratiksha Agarwal +2
Explaining the behavior of a black box machine learning model at the instance level is useful for building trust. However, it is also important to understand how the model behaves…