Search Results for author: Sahil Sharma

Found 10 papers, 1 papers with code

A Comprehensive Review on Summarizing Financial News Using Deep Learning

no code implementations21 Sep 2021 Saurabh Kamal, Sahil Sharma

Another factor on which investors can make investment decisions is through sentiment analysis of news headlines, the sole purpose of this study.

Sentiment Analysis

Challenges and Solutions in DeepFakes

no code implementations12 Sep 2021 Jatin Sharma, Sahil Sharma

Deep learning has been successfully appertained to solve various complex problems in the area of big data analytics to computer vision.

WAD: A Deep Reinforcement Learning Agent for Urban Autonomous Driving

no code implementations27 Aug 2021 Arjit Sharma, Sahil Sharma

Urban autonomous driving is an open and challenging problem to solve as the decision-making system has to account for several dynamic factors like multi-agent interactions, diverse scene perceptions, complex road geometries, and other rarely occurring real-world events.

Atari Games Autonomous Driving +3

Content Based Image Retrieval from AWiFS Images Repository of IRS Resourcesat-2 Satellite Based on Water Bodies and Burnt Areas

no code implementations26 Sep 2018 Suraj Kothawade, Kunjan Mhaske, Sahil Sharma, Furkhan Shaikh

Satellite Remote Sensing Technology is becoming a major milestone in the prediction of weather anomalies, natural disasters as well as finding alternative resources in proximity using multiple multi-spectral sensors emitting electromagnetic waves at distinct wavelengths.

Content-Based Image Retrieval Retrieval +1

Learning to Mix n-Step Returns: Generalizing lambda-Returns for Deep Reinforcement Learning

no code implementations ICLR 2018 Sahil Sharma, Girish Raguvir J, Srivatsan Ramesh, Balaraman Ravindran

Our second major contribution is that we propose a generalization of lambda-returns called Confidence-based Autodidactic Returns (CAR), wherein the RL agent learns the weighting of the n-step returns in an end-to-end manner.

Benchmarking Decision Making +2

Learning to Multi-Task by Active Sampling

1 code implementation ICLR 2018 Sahil Sharma, Ashutosh Jha, Parikshit Hegde, Balaraman Ravindran

In this work, we propose an efficient multi-task learning framework which solves multiple goal-directed tasks in an on-line setup without the need for expert supervision.

Active Learning Meta-Learning +1

Learning to Repeat: Fine Grained Action Repetition for Deep Reinforcement Learning

no code implementations20 Feb 2017 Sahil Sharma, Aravind Srinivas, Balaraman Ravindran

Reinforcement Learning algorithms can learn complex behavioral patterns for sequential decision making tasks wherein an agent interacts with an environment and acquires feedback in the form of rewards sampled from it.

Car Racing Decision Making +2

Performance Based Evaluation of Various Machine Learning Classification Techniques for Chronic Kidney Disease Diagnosis

no code implementations28 Jun 2016 Sahil Sharma, Vinod Sharma, Atul Sharma

In order to calculate efficiency, results of the prediction by candidate methods were compared with the actual medical results of the subject. The various metrics used for performance evaluation are predictive accuracy, precision, sensitivity and specificity.

BIG-bench Machine Learning General Classification +2

Dynamic Frame skip Deep Q Network

no code implementations17 May 2016 Aravind Srinivas, Sahil Sharma, Balaraman Ravindran

Deep Reinforcement Learning methods have achieved state of the art performance in learning control policies for the games in the Atari 2600 domain.

Atari Games

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