Virtual Audio System Customization Using Visual Matching of Ear Parameters. - Dmitry N. Zotkin; Ramani Duraiswami; Larry S. Davis; Ankur Mohan; Vikas C. Raykar (ICPR (3), 2002)

Tracking a moving speaker using excitation source information. - Vikas C. Raykar; Ramani Duraiswami; B. Yegnanarayana 001; S. R. Mahadeva Prasanna (INTERSPEECH, 2003)

Position calibration of audio sensors and actuators in a distributed computing platform. - Vikas C. Raykar; Igor Kozintsev; Rainer Lienhart (ACM Multimedia, 2003)

Automatic position calibration of multiple microphones. - Vikas C. Raykar; Ramani Duraiswami (ICASSP (4), 2004)

The manifolds of spatial hearing. - Ramani Duraiswami; Vikas C. Raykar (ICASSP (3), 2005)

Approximate expressions for the mean and the covariance of the maximum likelihood estimator for acoustic source localization. - Vikas C. Raykar; Ramani Duraiswami (ICASSP (3), 2005)

Position calibration of microphones and loudspeakers in distributed computing platforms. - Vikas C. Raykar; Igor Kozintsev; Rainer Lienhart (IEEE Trans. Speech Audio Process., 2005)

Speaker Localization Using Excitation Source Information in Speech. - Vikas C. Raykar; B. Yegnanarayana 001; S. R. Mahadeva Prasanna; Ramani Duraiswami (IEEE Trans. Speech Audio Process., 2005)

Fast optimal bandwidth selection for kernel density estimation. - Vikas C. Raykar; Ramani Duraiswami (SDM, 2006)

Multimodal Tracking for Smart Videoconferencing and Video Surveillance. - Dmitry N. Zotkin; Vikas C. Raykar; Ramani Duraiswami; Larry S. Davis (CVPR, 2007)

On Ranking in Survival Analysis: Bounds on the Concordance Index. - Vikas C. Raykar; Harald Steck; Balaji Krishnapuram; Cary Dehing-Oberije; Philippe Lambin (NIPS, 2007)

A fast algorithm for learning large scale preference relations. - Vikas C. Raykar; Ramani Duraiswami; Balaji Krishnapuram (AISTATS, 2007)

Scalable machine learning for massive datasets: Fast summation algorithms. - Vikas Chandrakant Raykar (2007)

Polyhedral classifier for target detection: a case study: colorectal cancer. - Murat Dundar; Matthias Wolf 001; Sarang Lakare; Marcos Salganicoff; Vikas C. Raykar (ICML, 2008)

Bayesian multiple instance learning: automatic feature selection and inductive transfer. - Vikas C. Raykar; Balaji Krishnapuram; Jinbo Bi; Murat Dundar; R. Bharat Rao (ICML, 2008)

Multiple-Instance Learning Improves CAD Detection of Masses in Digital Mammography. - Balaji Krishnapuram; Jonathan Stoeckel; Vikas C. Raykar; R. Bharat Rao; Philippe Bamberger; Eli Ratner; Nicolas Merlet; Inna Stainvas; Menahem Abramov; Alexandra Manevitch (Digital Mammography / IWDM, 2008)

Automatic online tuning for fast Gaussian summation. - Vlad I. Morariu; Balaji Vasan Srinivasan; Vikas C. Raykar; Ramani Duraiswami; Larry S. Davis (NIPS, 2008)

A Fast Algorithm for Learning a Ranking Function from Large-Scale Data Sets. - Vikas C. Raykar; Ramani Duraiswami; Balaji Krishnapuram (IEEE Trans. Pattern Anal. Mach. Intell., 2008)

Supervised learning from multiple experts: whom to trust when everyone lies a bit. - Vikas C. Raykar; Shipeng Yu; Linda H. Zhao; Anna K. Jerebko; Charles Florin; Gerardo Hermosillo Valadez; Luca Bogoni; Linda Moy (ICML, 2009)

Lung Nodule Detection. - Luca Bogoni; Jinbo Bi; Charles Florin; Anna K. Jerebko; Arun Krishnan; Sangmin Park; Vikas C. Raykar; Marcos Salganicoff (ImageCLEF, 2010)

A Multiple Instance Learning Approach toward Optimal Classification of Pathology Slides. - Murat Dundar; Sunil Badve; Vikas C. Raykar; Rohit K. Jain; Olcay Sertel; Metin N. Gurcan (ICPR, 2010)

Designing efficient cascaded classifiers: tradeoff between accuracy and cost. - Vikas C. Raykar; Balaji Krishnapuram; Shipeng Yu (KDD, 2010)

Learning From Crowds. - Vikas C. Raykar; Shipeng Yu; Linda H. Zhao; Gerardo Hermosillo Valadez; Charles Florin; Luca Bogoni; Linda Moy (J. Mach. Learn. Res., 2010)

Nonparametric prior for adaptive sparsity. - Vikas C. Raykar; Linda H. Zhao (AISTATS, 2010)

Robust Large Scale Prone-Supine Polyp Matching Using Local Features: A Metric Learning Approach. - Meizhu Liu; Le Lu 001; Jinbo Bi; Vikas C. Raykar; Matthias Wolf 001; Marcos Salganicoff (MICCAI (3), 2011)

Ranking annotators for crowdsourced labeling tasks. - Vikas C. Raykar; Shipeng Yu (NIPS, 2011)

Computerized Classification of Intraductal Breast Lesions Using Histopathological Images. - Murat Dundar; Sunil Badve; Gökhan Bilgin; Vikas C. Raykar; Rohit K. Jain; Olcay Sertel; Metin N. Gurcan (IEEE Trans. Biomed. Eng., 2011)

Learning to Locate Cortical Bone in MRI. - Gerardo Hermosillo Valadez; Vikas C. Raykar; Xiang Zhou 009 (MLMI, 2012)

Eliminating Spammers and Ranking Annotators for Crowdsourced Labeling Tasks. - Vikas C. Raykar; Shipeng Yu (J. Mach. Learn. Res., 2012)

Mining anatomical, physiological and pathological information from medical images. - Xiang Sean Zhou; Yiqiang Zhan; Vikas C. Raykar; Gerardo Hermosillo Valadez; Luca Bogoni; Zhigang Peng (SIGKDD Explor., 2012)

Sequential crowdsourced labeling as an epsilon-greedy exploration in a Markov Decision Process. - Vikas C. Raykar; Priyanka Agrawal (AISTATS, 2014)

Claims on demand - an initial demonstration of a system for automatic detection and polarity identification of context dependent claims in massive corpora. - Noam Slonim; Ehud Aharoni; Carlos Alzate; Roy Bar-Haim; Yonatan Bilu; Lena Dankin; Iris Eiron; Daniel Hershcovich; Shay Hummel; Mitesh M. Khapra; Tamar Lavee; Ran Levy 001; et al. (COLING (Demos), 2014)

An Autoencoder Approach to Learning Bilingual Word Representations. - A. P. Sarath Chandar; Stanislas Lauly; Hugo Larochelle; Mitesh M. Khapra; Balaraman Ravindran; Vikas C. Raykar; Amrita Saha (NIPS, 2014)

AUC dominant unsupervised ensemble of binary classifiers. - Priyanka Agrawal; Vikas C. Raykar; Amrita Saha (SDM, 2014)

Data Split Strategiesfor Evolving Predictive Models. - Vikas C. Raykar; Amrita Saha (ECML/PKDD (1), 2015)

Taxonomy grounded aggregation of classifiers with different label sets. - Amrita Saha; Sathish Indurthi; Shantanu Godbole; Subendhu Rongali; Vikas C. Raykar (CoRR, 2015)

An Empirical Evaluation of various Deep Learning Architectures for Bi-Sequence Classification Tasks. - Anirban Laha; Vikas C. Raykar (COLING, 2016)

GRASP: Rich Patterns for Argumentation Mining. - Eyal Shnarch; Ran Levy 001; Vikas C. Raykar; Noam Slonim (EMNLP, 2017)

Joint Learning of Correlated Sequence Labeling Tasks Using Bidirectional Recurrent Neural Networks. - Vardaan Pahuja; Anirban Laha; Shachar Mirkin; Vikas C. Raykar; Lili Kotlerman; Guy Lev (INTERSPEECH, 2017)

Joint Learning of Correlated Sequence Labelling Tasks Using Bidirectional Recurrent Neural Networks. - Vardaan Pahuja; Anirban Laha; Shachar Mirkin; Vikas C. Raykar; Lili Kotlerman; Guy Lev (CoRR, 2017)

DeepSolarEye: Power Loss Prediction and Weakly Supervised Soiling Localization via Fully Convolutional Networks for Solar Panels. - Sachin Mehta; Amar P. Azad; Saneem A. Chemmengath; Vikas Raykar; Shivkumar Kalyanaraman (WACV, 2018)

Learning Disentangled Multimodal Representations for the Fashion Domain. - Amrita Saha; Megha Nawhal; Mitesh M. Khapra; Vikas C. Raykar (WACV, 2018)

Styling with Attention to Details. - Ayushi Dalmia; Sachindra Joshi; Raghavendra Singh; Vikas Raykar (CoRR, 2018)

Multimodal Dialog for Browsing Large Visual Catalogs using Exploration-Exploitation Paradigm in a Joint Embedding Space. - Indrani Bhattacharya; Arkabandhu Chowdhury; Vikas C. Raykar (ICMR, 2019)

Multi-modal dialog for browsing large visual catalogs using exploration-exploitation paradigm in a joint embedding space. - Indrani Bhattacharya; Arkabandhu Chowdhury; Vikas C. Raykar (CoRR, 2019)

Attention based Multi-Modal New Product Sales Time-series Forecasting. - Vijay Ekambaram; Kushagra Manglik; Sumanta Mukherjee; Surya Shravan Kumar Sajja; Satyam Dwivedi; Vikas Raykar (KDD, 2020)

Hyper-local sustainable assortment planning. - Nupur Aggarwal; Abhishek Bansal 004; Kushagra Manglik; Kedar Kulkarni; Vikas Raykar (CoRR, 2020)

Explainable AI based Interventions for Pre-season Decision Making in Fashion Retail. - Shravan Sajja; Nupur Aggarwal; Sumanta Mukherjee; Kushagra Manglik; Satyam Dwivedi; Vikas Raykar (COMAD/CODS, 2021)

TsSHAP: Robust model agnostic feature-based explainability for time series forecasting. - Vikas C. Raykar; Arindam Jati; Sumanta Mukherjee; Nupur Aggarwal; Kanthi K. Sarpatwar; Giridhar Ganapavarapu; Roman Vaculín (CoRR, 2023)

Graph-Based Algorithms for Diverse Similarity Search. - Piyush Anand; Piotr Indyk; Ravishankar Krishnaswamy; Sepideh Mahabadi; Vikas C. Raykar; Kirankumar Shiragur; Haike Xu (CoRR, 2025)