Search Results for author: Anirban Dasgupta

Found 26 papers, 6 papers with code

Faster Inference Time for GNNs using coarsening

1 code implementation19 Oct 2024 Shubhajit Roy, Hrriday Ruparel, Kishan Ved, Anirban Dasgupta

We propose a novel approach for using the coarsening algorithm for graph-level tasks such as graph classification and graph regression.

Graph Classification Graph Regression +2

Simple Weak Coresets for Non-Decomposable Classification Measures

no code implementations15 Dec 2023 Jayesh Malaviya, Anirban Dasgupta, Rachit Chhaya

While coresets have been growing in terms of their application, barring few exceptions, they have mostly been limited to unsupervised settings.

Classification

A Novel Pipeline for Improving Optical Character Recognition through Post-processing Using Natural Language Processing

no code implementations9 Jul 2023 Aishik Rakshit, Samyak Mehta, Anirban Dasgupta

Optical Character Recognition (OCR) technology finds applications in digitizing books and unstructured documents, along with applications in other domains such as mobility statistics, law enforcement, traffic, security systems, etc.

Optical Character Recognition Optical Character Recognition (OCR)

OSSuM: A Gradient-Free Approach For Pruning Neural Networks At Initialization

no code implementations29 Sep 2021 Vinu Sankar Sadasivan, Jayesh Malaviya, Anirban Dasgupta

Recent works attempt to prune neural networks at initialization to design sparse networks that can be trained efficiently.

Statistical Measures For Defining Curriculum Scoring Function

1 code implementation27 Feb 2021 Vinu Sankar Sadasivan, Anirban Dasgupta

Curriculum learning is a training strategy that sorts the training examples by some measure of their difficulty and gradually exposes them to the learner to improve the network performance.

Image Classification

A Simple Approach To Define Curricula For Training Neural Networks

no code implementations1 Jan 2021 Vinu Sankar Sadasivan, Anirban Dasgupta

Curriculum learning is a training strategy that sorts the training examples by their difficulty and gradually exposes them to the learner.

Online Coresets for Clustering with Bregman Divergences

no code implementations11 Dec 2020 Rachit Chhaya, Jayesh Choudhari, Anirban Dasgupta, Supratim Shit

Our first algorithm gives online coresets of size $\tilde{O}(\mbox{poly}(k, d,\epsilon,\mu))$ for $k$-clusterings according to any $\mu$-similar Bregman divergence.

Clustering

On Additive Approximate Submodularity

no code implementations6 Oct 2020 Flavio Chierichetti, Anirban Dasgupta, Ravi Kumar

We show that an approximately submodular function defined on a ground set of $n$ elements is $O(n^2)$ pointwise-close to a submodular function.

On Coresets For Regularized Regression

1 code implementation ICML 2020 Rachit Chhaya, Anirban Dasgupta, Supratim Shit

We propose a modified version of the lasso problem and obtain for it a coreset of size smaller than the least square regression.

regression

Streaming Coresets for Symmetric Tensor Factorization

1 code implementation ICML 2020 Rachit Chhaya, Jayesh Choudhari, Anirban Dasgupta, Supratim Shit

Factorizing tensors has recently become an important optimization module in a number of machine learning pipelines, especially in latent variable models.

Mallows Models for Top-k Lists

no code implementations NeurIPS 2018 Flavio Chierichetti, Anirban Dasgupta, Shahrzad Haddadan, Ravi Kumar, Silvio Lattanzi

The classic Mallows model is a widely-used tool to realize distributions on per- mutations.

Discovering Topical Interactions in Text-based Cascades using Hidden Markov Hawkes Processes

no code implementations12 Sep 2018 Srikanta Bedathur, Indrajit Bhattacharya, Jayesh Choudhari, Anirban Dasgupta

We show using experiments on real and semi-synthetic data that HMHP is able to generalize better and recover the network strengths, topics and diffusion paths more accurately than state-of-the-art baselines.

Improved Linear Embeddings via Lagrange Duality

no code implementations30 Nov 2017 Kshiteej Sheth, Dinesh Garg, Anirban Dasgupta

Near isometric orthogonal embeddings to lower dimensions are a fundamental tool in data science and machine learning.

An Improved Algorithm for Eye Corner Detection

no code implementations16 Sep 2015 Anirban Dasgupta, Anshit Mandloi, Anjith George, Aurobinda Routray

In this paper, a modified algorithm for the detection of nasal and temporal eye corners is presented.

Evaluation of Denoising Techniques for EOG signals based on SNR Estimation

no code implementations16 Jun 2015 Anirban Dasgupta, Suvodip Chakrborty, Aritra Chaudhuri, Aurobinda Routray

This paper evaluates four algorithms for denoising raw Electrooculography (EOG) data based on the Signal to Noise Ratio (SNR).

Denoising

Fast Computation of PERCLOS and Saccadic Ratio

no code implementations29 May 2015 Anirban Dasgupta, Aurobinda Routray

This thesis describes the development of fast algorithms for the computation of PERcentage CLOSure of eyes (PERCLOS) and Saccadic Ratio (SR).

A Framework for Fast Face and Eye Detection

no code implementations13 May 2015 Anjith George, Anirban Dasgupta, Aurobinda Routray

Face detection is an essential step in many computer vision applications like surveillance, tracking, medical analysis, facial expression analysis etc.

Face Detection

A Vision Based System for Monitoring the Loss of Attention in Automotive Drivers

no code implementations13 May 2015 Anirban Dasgupta, Anjith George, S. L. Happy, Aurobinda Routray

In this paper, we propose a robust real time embedded platform to monitor the loss of attention of the driver during day as well as night driving conditions.

Management

Crowdsourced judgement elicitation with endogenous proficiency

1 code implementation WWW 2013 Anirban Dasgupta, Arpita Ghosh

Our main contribution is a simple, new, mechanism for binary information elicitation for multiple tasks when agents have endogenous proficiencies, with the following properties: (i) Exerting maximum effort followed by truthful reporting of observations is a Nash equilibrium.

Selecting Diverse Features via Spectral Regularization

no code implementations NeurIPS 2012 Abhimanyu Das, Anirban Dasgupta, Ravi Kumar

We compare our algorithms to traditional greedy and $\ell_1$-regularization schemes and show that we obtain a more diverse set of features that result in the regression problem being stable under perturbations.

Diversity feature selection +1

Feature Hashing for Large Scale Multitask Learning

no code implementations12 Feb 2009 Kilian Weinberger, Anirban Dasgupta, Josh Attenberg, John Langford, Alex Smola

Empirical evidence suggests that hashing is an effective strategy for dimensionality reduction and practical nonparametric estimation.

Dimensionality Reduction

Community Structure in Large Networks: Natural Cluster Sizes and the Absence of Large Well-Defined Clusters

no code implementations8 Oct 2008 Jure Leskovec, Kevin J. Lang, Anirban Dasgupta, Michael W. Mahoney

A large body of work has been devoted to defining and identifying clusters or communities in social and information networks.

Data Structures and Algorithms Data Analysis, Statistics and Probability Physics and Society

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