Search Results for author: Sourangshu Bhattacharya

Found 18 papers, 7 papers with code

Learning Cross-Task Attribute - Attribute Similarity for Multi-task Attribute-Value Extraction

no code implementations ACL (ECNLP) 2021 Mayank Jain, Sourangshu Bhattacharya, Harshit Jain, Karimulla Shaik, Muthusamy Chelliah

We perform detailed experiments to show that our method indeed increases the macro-F1 scores for attribute value extraction in general, and for labels with low training data in particular.

Attribute Value Extraction Multi-Task Learning

Modeling Continuous Time Sequences with Intermittent Observations using Marked Temporal Point Processes

1 code implementation23 Jun 2022 Vinayak Gupta, Srikanta Bedathur, Sourangshu Bhattacharya, Abir De

In this work, we provide a novel unsupervised model and inference method for learning MTPP in presence of event sequences with missing events.

Point Processes Variational Inference

CheckSel: Efficient and Accurate Data-valuation Through Online Checkpoint Selection

no code implementations14 Mar 2022 Soumi Das, Manasvi Sagarkar, Suparna Bhattacharya, Sourangshu Bhattacharya

Another key contribution is the study of data valuation in the domain adaptation setting, where a data value estimator obtained using checkpoints from training trajectory in the source domain training dataset is used for data valuation in a target domain training dataset.

Domain Adaptation

Offsetting Unequal Competition through RL-assisted Incentive Schemes

no code implementations5 Jan 2022 Paramita Koley, Aurghya Maiti, Sourangshu Bhattacharya, Niloy Ganguly

On inspecting, we realize that an overall incentive scheme for the weak team does not incentivize the weaker agents within that team to learn and improve.

Multi-agent Reinforcement Learning reinforcement-learning

PASTE: A Tagging-Free Decoding Framework Using Pointer Networks for Aspect Sentiment Triplet Extraction

1 code implementation EMNLP 2021 Rajdeep Mukherjee, Tapas Nayak, Yash Butala, Sourangshu Bhattacharya, Pawan Goyal

Aspect Sentiment Triplet Extraction (ASTE) deals with extracting opinion triplets, consisting of an opinion target or aspect, its associated sentiment, and the corresponding opinion term/span explaining the rationale behind the sentiment.

Aspect Sentiment Triplet Extraction

AR-BERT: Aspect-relation enhanced Aspect-level Sentiment Classification with Multi-modal Explanations

2 code implementations26 Aug 2021 Sk Mainul Islam, Sourangshu Bhattacharya

We propose AR-BERT, a novel two-level global-local entity embedding scheme that allows efficient joint training of KG-based aspect embeddings and ALSC models.

Aspect-Based Sentiment Analysis Explanation Generation +1

Convex Online Video Frame Subset Selection using Multiple Criteria for Data Efficient Autonomous Driving

no code implementations24 Mar 2021 Soumi Das, Harikrishna Patibandla, Suparna Bhattacharya, Kshounis Bera, Niloy Ganguly, Sourangshu Bhattacharya

We design a novel convex optimization-based multi-criteria online subset selection algorithm that uses a thresholded concave function of selection variables.

Autonomous Driving

Demarcating Endogenous and Exogenous Opinion Dynamics: An Experimental Design Approach

no code implementations11 Feb 2021 Paramita Koley, Avirup Saha, Sourangshu Bhattacharya, Niloy Ganguly, Abir De

The networked opinion diffusion in online social networks (OSN) is often governed by the two genres of opinions - endogenous opinions that are driven by the influence of social contacts among users, and exogenous opinions which are formed by external effects like news, feeds etc.

Experimental Design

Scalable Backdoor Detection in Neural Networks

no code implementations10 Jun 2020 Haripriya Harikumar, Vuong Le, Santu Rana, Sourangshu Bhattacharya, Sunil Gupta, Svetha Venkatesh

Recently, it has been shown that deep learning models are vulnerable to Trojan attacks, where an attacker can install a backdoor during training time to make the resultant model misidentify samples contaminated with a small trigger patch.

SPIN: A Fast and Scalable Matrix Inversion Method in Apache Spark

1 code implementation15 Jan 2018 Chandan Misra, Sourangshu Bhattacharya, Soumya K. Ghosh

The growth of big data in domains such as Earth Sciences, Social Networks, Physical Sciences, etc.

Distributed, Parallel, and Cluster Computing

A Methodology for Customizing Clinical Tests for Esophageal Cancer based on Patient Preferences

no code implementations6 Oct 2016 Asis Roy, Sourangshu Bhattacharya, Kalyan Guin

Our objective is to devise a general methodology for customizing tests using user preferences so that expensive or uncomfortable tests can be avoided.

General Classification

Distributed Weighted Parameter Averaging for SVM Training on Big Data

no code implementations30 Sep 2015 Ayan Das, Sourangshu Bhattacharya

Experimental results on a variety of toy and real world datasets show that our approach is significantly more accurate than parameter averaging for high number of partitions.

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