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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...
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05/18/2023
STREAMLINE: Streaming Active Learning for Realistic Multi-Distributional Settings
Deep neural networks have consistently shown great performance in severa...
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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...
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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...
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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...
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10/04/2022
DIAGNOSE: Avoiding Out-of-distribution Data using Submodular Information Measures
Avoiding out-of-distribution (OOD) data is critical for training supervi...
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10/04/2022
CLINICAL: Targeted Active Learning for Imbalanced Medical Image Classification
Training deep learning models on medical datasets that perform well for ...
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06/17/2022
Active Data Discovery: Mining Unknown Data using Submodular Information Measures
Active Learning is a very common yet powerful framework for iteratively ...
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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...
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03/10/2022
BASIL: Balanced Active Semi-supervised Learning for Class Imbalanced Datasets
Current semi-supervised learning (SSL) methods assume a balance between ...
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02/22/2022
Submodlib: A Submodular Optimization Library
Submodular functions are a special class of set functions which naturall...
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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...
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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 ...
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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...
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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...
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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...
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08/06/2021
Independence Properties of Generalized Submodular Information Measures
Recently a class of generalized information measures was defined on sets...
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08/01/2021
SPEAR : Semi-supervised Data Programming in Python
We present SPEAR, an open-source python library for data programming wit...
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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...
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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...
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06/14/2021
RETRIEVE: Coreset Selection for Efficient and Robust Semi-Supervised Learning
Semi-supervised learning (SSL) algorithms have had great success in rece...
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06/03/2021
BiFair: Training Fair Models with Bilevel Optimization
Prior studies have shown that, training machine learning models via empi...
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05/21/2021
Rule Augmented Unsupervised Constituency Parsing
Recently, unsupervised parsing of syntactic trees has gained considerabl...
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04/30/2021
Submodular Mutual Information for Targeted Data Subset Selection
With the rapid growth of data, it is becoming increasingly difficult to ...
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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...
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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...
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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. ...
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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...
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10/16/2020
Deep Submodular Networks for Extractive Data Summarization
Deep Models are increasingly becoming prevalent in summarization problem...
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10/14/2020
Improving Accuracy of Federated Learning in Non-IID Settings
Federated Learning (FL) is a decentralized machine learning protocol tha...
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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...
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10/07/2020
Robust Semi-Supervised Learning with Out of Distribution Data
Semi-supervised learning (SSL) based on deep neural networks (DNNs) has ...
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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...
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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...
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06/27/2020
Submodular Combinatorial Information Measures with Applications in Machine Learning
Information-theoretic quantities like entropy and mutual information hav...
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06/27/2020
Concave Aspects of Submodular Functions
Submodular Functions are a special class of set functions, which general...
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01/25/2020
Robust Submodular Minimization with Applications to Cooperative Modeling
Robust Optimization is becoming increasingly important in machine learni...
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06/14/2019
A Unified Framework of Robust Submodular Optimization
In this paper, we shall study a unified framework of robust submodular o...
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02/26/2019
A Memoization Framework for Scaling Submodular Optimization to Large Scale Problems
We are motivated by large scale submodular optimization problems, where ...
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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...
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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...
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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...
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09/24/2018
A Framework towards Domain Specific Video Summarization
In the light of exponentially increasing video content, video summarizat...
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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...
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09/12/2018
A Unified Batch Online Learning Framework for Click Prediction
We present a unified framework for Batch Online Learning (OL) for Click ...
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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 ...
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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...
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05/27/2018
Deployment of Customized Deep Learning based Video Analytics On Surveillance Cameras
This paper demonstrates the effectiveness of our customized deep learnin...
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04/18/2018
Modeling and Simultaneously Removing Bias via Adversarial Neural Networks
In real world systems, the predictions of deployed Machine Learned model...
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04/04/2017
