b'Rishabh Iyer'

research

∙ 06/02/2023

Beyond Active Learning: Leveraging the Full Potential of Human Interaction via Auto-Labeling, Human Correction, and Human Verification

Active Learning (AL) is a human-in-the-loop framework to interactively a...

0 Nathan Beck, et al. ∙

research

∙ 05/18/2023

STREAMLINE: Streaming Active Learning for Realistic Multi-Distributional Settings

Deep neural networks have consistently shown great performance in severa...

0 Nathan Beck, et al. ∙

research

∙ 05/11/2023

INGENIOUS: Using Informative Data Subsets for Efficient Pre-Training of Large Language Models

A salient characteristic of large pre-trained language models (PTLMs) is...

0 H S V N S Kowndinya Renduchintala, et al. ∙

research

∙ 01/30/2023

MILO: Model-Agnostic Subset Selection Framework for Efficient Model Training and Tuning

Training deep networks and tuning hyperparameters on large datasets is c...

0 Kirshnateja Killamsetty, et al. ∙

research

∙ 10/30/2022

Partitioned Gradient Matching-based Data Subset Selection for Compute-Efficient Robust ASR Training

Training state-of-the-art ASR systems such as RNN-T often has a high ass...

0 Ashish Mittal, et al. ∙

research

∙ 10/04/2022

DIAGNOSE: Avoiding Out-of-distribution Data using Submodular Information Measures

Avoiding out-of-distribution (OOD) data is critical for training supervi...

0 Suraj Kothawade, et al. ∙

research

∙ 10/04/2022

CLINICAL: Targeted Active Learning for Imbalanced Medical Image Classification

Training deep learning models on medical datasets that perform well for ...

0 Suraj Kothawade, et al. ∙

research

∙ 06/17/2022

Active Data Discovery: Mining Unknown Data using Submodular Information Measures

Active Learning is a very common yet powerful framework for iteratively ...

0 Suraj Kothawade, et al. ∙

research

∙ 03/15/2022

AUTOMATA: Gradient Based Data Subset Selection for Compute-Efficient Hyper-parameter Tuning

Deep neural networks have seen great success in recent years; however, t...

0 KrishnaTeja Killamsetty, et al. ∙

research

∙ 03/10/2022

BASIL: Balanced Active Semi-supervised Learning for Class Imbalanced Datasets

Current semi-supervised learning (SSL) methods assume a balance between ...

0 Suraj Kothawade, et al. ∙

research

∙ 02/22/2022

Submodlib: A Submodular Optimization Library

Submodular functions are a special class of set functions which naturall...

0 Vishal Kaushal, et al. ∙

research

∙ 01/30/2022

PLATINUM: Semi-Supervised Model Agnostic Meta-Learning using Submodular Mutual Information

Few-shot classification (FSC) requires training models using a few (typi...

1 Changbin Li, et al. ∙

research

∙ 11/30/2021

TALISMAN: Targeted Active Learning for Object Detection with Rare Classes and Slices using Submodular Mutual Information

Deep neural networks based object detectors have shown great success in ...

0 Suraj Kothawade, et al. ∙

research

∙ 11/18/2021

GCR: Gradient Coreset Based Replay Buffer Selection For Continual Learning

Continual learning (CL) aims to develop techniques by which a single mod...

1 Rishabh Tiwari, et al. ∙

research

∙ 10/10/2021

Personalizing ASR with limited data using targeted subset selection

We study the task of personalizing ASR models to a target non-native spe...

0 Mayank Kothyari, et al. ∙

research

∙ 09/23/2021

Learning to Robustly Aggregate Labeling Functions for Semi-supervised Data Programming

A critical bottleneck in supervised machine learning is the need for lar...

1 Ayush Maheshwari, et al. ∙

research

∙ 08/06/2021

Independence Properties of Generalized Submodular Information Measures

Recently a class of generalized information measures was defined on sets...

0 Himanshu Asnani, et al. ∙

research

∙ 08/01/2021

SPEAR : Semi-supervised Data Programming in Python

We present SPEAR, an open-source python library for data programming wit...

0 Guttu Sai Abhishek, et al. ∙

research

∙ 07/01/2021

SIMILAR: Submodular Information Measures Based Active Learning In Realistic Scenarios

Active learning has proven to be useful for minimizing labeling costs by...

2 Suraj Kothawade, et al. ∙

research

∙ 06/23/2021

Training Data Subset Selection for Regression with Controlled Generalization Error

Data subset selection from a large number of training instances has been...

0 Durga Sivasubramanian, et al. ∙

research

∙ 06/14/2021

RETRIEVE: Coreset Selection for Efficient and Robust Semi-Supervised Learning

Semi-supervised learning (SSL) algorithms have had great success in rece...

11 KrishnaTeja Killamsetty, et al. ∙

research

∙ 06/03/2021

BiFair: Training Fair Models with Bilevel Optimization

Prior studies have shown that, training machine learning models via empi...

0 Mustafa Safa Ozdayi, et al. ∙

research

∙ 05/21/2021

Rule Augmented Unsupervised Constituency Parsing

Recently, unsupervised parsing of syntactic trees has gained considerabl...

0 Atul Sahay, et al. ∙

research

∙ 04/30/2021

Submodular Mutual Information for Targeted Data Subset Selection

With the rapid growth of data, it is becoming increasingly difficult to ...

0 Suraj Kothawade, et al. ∙

research

∙ 02/27/2021

PRISM: A Unified Framework of Parameterized Submodular Information Measures for Targeted Data Subset Selection and Summarization

With increasing data, techniques for finding smaller, yet effective subs...

0 Vishal Kaushal, et al. ∙

research

∙ 01/26/2021

How Good is a Video Summary? A New Benchmarking Dataset and Evaluation Framework Towards Realistic Video Summarization

Automatic video summarization is still an unsolved problem due to severa...

0 Vishal Kaushal, et al. ∙

research

∙ 12/19/2020

GLISTER: Generalization based Data Subset Selection for Efficient and Robust Learning

Large scale machine learning and deep models are extremely data-hungry. ...

1 KrishnaTeja Killamsetty, et al. ∙

research

∙ 11/13/2020

A Reweighted Meta Learning Framework for Robust Few Shot Learning

Model-Agnostic Meta-Learning (MAML) is a popular gradient-based meta-lea...

7 KrishnaTeja Killamsetty, et al. ∙

research

∙ 10/16/2020

Deep Submodular Networks for Extractive Data Summarization

Deep Models are increasingly becoming prevalent in summarization problem...

0 Suraj Kothawade, et al. ∙

research

∙ 10/14/2020

Improving Accuracy of Federated Learning in Non-IID Settings

Federated Learning (FL) is a decentralized machine learning protocol tha...

0 Mustafa Safa Ozdayi, et al. ∙

research

∙ 10/12/2020

A Unified Framework for Generic, Query-Focused, Privacy Preserving and Update Summarization using Submodular Information Measures

We study submodular information measures as a rich framework for generic...

2 Vishal Kaushal, et al. ∙

research

∙ 10/07/2020

Robust Semi-Supervised Learning with Out of Distribution Data

Semi-supervised learning (SSL) based on deep neural networks (DNNs) has ...

10 Xujiang Zhao, et al. ∙

research

∙ 08/22/2020

Data Programming using Semi-Supervision and Subset Selection

The paradigm of data programming <cit.> has shown a lot of promise in us...

14 Ayush Maheshwari, et al. ∙

research

∙ 07/29/2020

Realistic Video Summarization through VISIOCITY: A New Benchmark and Evaluation Framework

Automatic video summarization is still an unsolved problem due to severa...

1 Vishal Kaushal, et al. ∙

research

∙ 06/27/2020

Submodular Combinatorial Information Measures with Applications in Machine Learning

Information-theoretic quantities like entropy and mutual information hav...

0 Rishabh Iyer, et al. ∙

research

∙ 06/27/2020

Concave Aspects of Submodular Functions

Submodular Functions are a special class of set functions, which general...

0 Rishabh Iyer, et al. ∙

research

∙ 01/25/2020

Robust Submodular Minimization with Applications to Cooperative Modeling

Robust Optimization is becoming increasingly important in machine learni...

0 Rishabh Iyer, et al. ∙

research

∙ 06/14/2019

A Unified Framework of Robust Submodular Optimization

In this paper, we shall study a unified framework of robust submodular o...

0 Rishabh Iyer, et al. ∙

research

∙ 02/26/2019

A Memoization Framework for Scaling Submodular Optimization to Large Scale Problems

We are motivated by large scale submodular optimization problems, where ...

0 Rishabh Iyer, et al. ∙

research

∙ 02/26/2019

Near Optimal Algorithms for Hard Submodular Programs with Discounted Cooperative Costs

In this paper, we investigate a class of submodular problems which in ge...

0 Rishabh Iyer, et al. ∙

research

∙ 01/03/2019

Learning From Less Data: A Unified Data Subset Selection and Active Learning Framework for Computer Vision

Supervised machine learning based state-of-the-art computer vision techn...

0 Vishal Kaushal, et al. ∙

research

∙ 01/03/2019

Demystifying Multi-Faceted Video Summarization: Tradeoff Between Diversity,Representation, Coverage and Importance

This paper addresses automatic summarization of videos in a unified mann...

0 Vishal Kaushal, et al. ∙

research

∙ 09/24/2018

A Framework towards Domain Specific Video Summarization

In the light of exponentially increasing video content, video summarizat...

0 Vishal Kaushal, et al. ∙

research

∙ 09/24/2018

Vis-DSS: An Open-Source toolkit for Visual Data Selection and Summarization

With increasing amounts of visual data being created in the form of vide...

0 Rishabh Iyer, et al. ∙

research

∙ 09/12/2018

A Unified Batch Online Learning Framework for Click Prediction

We present a unified framework for Batch Online Learning (OL) for Click ...

0 Rishabh Iyer, et al. ∙

research

∙ 07/17/2018

Jensen: An Easily-Extensible C++ Toolkit for Production-Level Machine Learning and Convex Optimization

This paper introduces Jensen, an easily extensible and scalable toolkit ...

2 Rishabh Iyer, et al. ∙

research

∙ 05/28/2018

Learning From Less Data: Diversified Subset Selection and Active Learning in Image Classification Tasks

Supervised machine learning based state-of-the-art computer vision techn...

0 Vishal Kaushal, et al. ∙

research

∙ 05/27/2018

Deployment of Customized Deep Learning based Video Analytics On Surveillance Cameras

This paper demonstrates the effectiveness of our customized deep learnin...

0 Pratik Dubal, et al. ∙

research

∙ 04/18/2018

Modeling and Simultaneously Removing Bias via Adversarial Neural Networks

In real world systems, the predictions of deployed Machine Learned model...

0 John Moore, et al. ∙

research

∙ 04/04/2017

A Unified Multi-Faceted Video Summarization System

This paper addresses automatic summarization and search in visual data c...

0 Anurag Sahoo, et al. ∙

Rishabh Iyer

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