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To appear
Empirical bayesian thresholding for sparse signals using mixture loss functions Vikas C. Raykar, and Linda H. Zhao To appear in Statistica Sinica [preprint]
2010
A Multiple Instance Learning Approach toward Optimal Classification of Pathology Slides Murat Dundar, Sunil Badve, Vikas C. Raykar, Rohit Jain, Olcay Sertel, and Metin Gurcan, Proceedings of 20th International Conference on Pattern Recognition [preprint] [bib] [acceptance rate 18%] [Best Scientific Paper Award in Bioinformatics and Biomedical Applications Track]
Designing efficient cascaded classifiers: Tradeoff between accuracy and cost Vikas C. Raykar, Balaji Krishnapuram, and Shipeng Yu, Proceedings of the 16th ACM SIGKDD international conference on Knowledge discovery and data mining (KDD'10), pp.853-860, Washington DC, July 2010. [abstract] [paper] [slides] [bib] [acceptance rate 17%] [oral presentation]
Learning from crowds Vikas C. Raykar, Shipeng Yu, Linda H. Zhao, Gerardo Valadez, Charles Florin, Luca Bogoni, and Linda Moy, Journal of Machine Learning Research, 11(Apr):1297−1322, 2010 [abstract] [paper] [bib]
Nonparametric prior for adaptive sparsity Vikas C. Raykar and Linda H. Zhao, Proceedings of the Thirteenth International Conference on Artificial Intelligence and Statistics (AISTATS) 2010, JMLR: W&CP 9, pp.629-636, Chia Laguna, Sardinia, Italy, May 13-15, 2010 [abstract] [paper] [slides] [bib]
Fast Computation of Kernel Estimators Vikas C. Raykar, Ramani Duraiswami, and Linda H. Zhao, Journal of Computational and Graphical Statistics. March 2010, Vol. 19, No. 1: 205-220 [abstract] [paper] [bib]
Lung Nodule Detection Luca Bogoni, Jinbo Bi, Charles Florin, Anna K.
Jerebko, Arun Krishnan, Sangmin Park,
Vikas C. Raykar,
and Marcos Salganicoff, Book Chapter in ImageCLEF: Experimental
Evaluation in Visual Information Retrieval, 2010, Volume 32, Part 3, pp
415-434, Springer Berlin Heidelberg. [abstract] [paper]
[bib]
CT colonography:
Retrospective evaluation of the performance of computer-aided detection
of colonic polyps in tagged and untagged preparation T.
Mang, L. Bogoni, M. Salganicoff, M. Wolf, V. Raykar, M. Macari, and A. Graser,
In the annual meeting of the European Congress of Radiology (ECR),
March 2010.
[abstract]
[proceedings]
Effect of a concurrent virtual dissection with CAD for CTC interpretation: A multi-reader study evaluating accuracy and interpretation times A.A. Ahmad, M. Macari, K.C. Cho, J.A. Bonavita, E. Robinson, L. Bogoni, M. Salganicoff, M. Wolf, and V. Raykar, In the annual meeting of the European Congress of Radiology (ECR), March 2010. [abstract] [proceedings]
2009
Mining Medical
Images R. Bharat Rao,
Glenn Fung, Balaji
Krishnapuram, Jinbo Bi, Murat Dundar, Vikas C. Raykar, Shipeng Yu,
Sriram Krishnan, Xiang Zhou, Arun Krishnan, Marcos Salganicoff, Luca
Bogoni, Matthias Wolf, Anna Jerebko, and Jonathan Stoeckel, In
Proceedings of the Third Workshop on Data Mining Case Studies and
Practice Prize, Fifteenth Annual SIGKDD International Conference on
Knowledge Discovery and Data Mining (KDD 2009), Paris, June 2009.
[paper] [slides] [bib] [First
place prize winner]
Supervised Learning from Multiple Experts: Whom to trust when everyone lies a bit Vikas C. Raykar, Shipeng Yu, Linda Zhao, Anna Jerebko, Charles Florin, Gerardo Valadez, Luca Bogoni, and Linda Moy, In Proceedings of the 26th International Conference on Machine Learning (ICML 2009), pp.889-896, Montreal, June 2009. [paper] [discussion] [slides] [bib]
Assessment of
Computer-aided Nodule Detection (CAD) Algorithm on Pathology Proved CT
Data Sets Vikas C.
Raykar, Sangmin Park, Tae
Jung Kim, Vikas C. Raykar, Vikram Anand, Maneesh Dewan, and
Anna Jerebko, In Radiological Society of North America scientific
assembly and annual meeting program (RSNA 2008), November
2008. [abstract]
[oral presentation]
2008
A fast algorithm for learning a ranking function from large scale data sets Vikas C. Raykar, Ramani Duraiswami, and Balaji Krishnapuram, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 30, no. 7, pp. 1158-1170, July 2008. [paper]
Automatic online tuning for fast Gaussian summation Vlad I. Morariu, Balaji V. Srinivasan, Vikas C. Raykar, Ramani Duraiswami, and Larry Davis, In Advances in Neural Information Processing Systems (NIPS 2008), vol. 21, pp.1113-1120, 2009. [paper] [spotlight slide] [bib] [code]
Bayesian Multiple Instance Learning: Automatic Feature Selection and Inductive Transfer Vikas C. Raykar, Balaji Krishnapuram, Jinbo Bi, Murat Dundar, and R. Bharat Rao, In Proceedings of the 25th International Conference on Machine Learning (ICML 2008), pp.808-815, Helsinki, July 2008. [paper] [slides] [bib]
Polyhedral Classifier for
Target Detection A Case Study: Colorectal Cancer Murat Dundar, Matthias Wolf, Sarang Lakare,
Marcos Salganicoff, and Vikas C. Raykar, In Proceedings of the
25th International Conference on Machine Learning (ICML 2008),
pp.288-295, Helsinki, July 2008. [paper] [slides]
[bib]
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, and Alexandra Manevitch, In Proceedings of the 9th international workshop on Digital Mammography (IWDM 2008), pp.350-357, Tucson, AZ, July 2008. [paper] [slides] [bib] [oral presentation]
Efficient Kriging via
Fast Matrix-Vector Products Nargess
Memarsadeghi, Vikas C. Raykar, Ramani Duraiswami, and David M.
Mount. In IEEE Aerospace Conference, Big Sky, Montana, March 2008.
[paper]
2007
On Ranking in Survival Analysis: Bounds on the Concordance Index Vikas C. Raykar, Harald Steck, Balaji Krishnapuram, Cary Dehing-Oberije, and Philippe Lambin. In Advances in Neural Information Processing Systems, vol. 20, pp. 1209–1216 , 2008. [paper] [slides] [spotlight slide] [bib]
A fast algorithm for learning large scale preference relations. Vikas C. Raykar, Ramani Duraiswami, and Balaji Krishnapuram, In Proceedings of the Eleventh International Conference on Artificial Intelligence and Statistics, San Juan, Peurto Rico, March 2007, pp. 385-392. [paper] [slides] [code] [bib] [ More details can be found in CS-TR-4848 ] [oral presentation]
Fast optimal bandwidth selection for kernel density estimation. Vikas C. Raykar and Ramani Duraiswami, In Proceedings of the sixth SIAM International Conference on Data Mining, Bethesda, April 2006, pp. 524-528. [paper] [brief slides] [code] [bib] [ Detailed version available as CS-TR-4774 ]
The Improved Fast Gauss Transform with applications to machine learning Vikas C. Raykar, and Ramani Duraiswami, To appear in Large Scale Kernel Machines L. Bottou, O. Chapelle, D. Decoste, and J. Weston (Eds), MIT Press 2006. [chapter]
Fast large scale Gaussian process regression using approximate matrix-vector products. Vikas C. Raykar and Ramani Duraiswami, Presented at the Learning workshop 2007, San Juan, Peurto Rico, March 2007. [abstract] [detailed paper] [slides]
Multimodal tracking for smart videoconferencing and video surveillance Dmitry Zotkin, Vikas C. Raykar, Ramani Duraiswami and Larry S. Davis. In Multimodal Surveillance: Sensors, Algorithms, and Systems, ed. by Zhihang Zhu and Thomas S. Huang, Artech House Publishers, Norwood, MA, 2007, pp. 141-175.
On the manifolds of spatial hearing. Vikas C. Raykar and Ramani Duraiswami, Presented at the NIPS 2006 workshop on Novel Applications of Dimensionality Reduction. [abstract] [slides]
The improved fast Gauss Transform with applications to machine learning. Vikas C. Raykar and Ramani Duraiswami, Presented at the NIPS 2005 workshop on Large scale kernel machines. [slides] [code] [video]
2005 and earlier
The manifolds of spatial hearing Ramani Duraiswami and
Vikas C. Raykar, In Proceedings of International Conference on
Acoustics, Speech and Signal Processing (ICASSP
2005), Philadelphia, March 2005, vol. III, pp. 285-288
[
Slides ]
Approximate expressions for the mean
and the covariance of the maximum likelihood estimator for acoustic
source localization Vikas C. Raykar and Ramani Duraiswami, In
Proceedings of International Conference on Acoustics, Speech and Signal
Processing (ICASSP 2005), Philadelphia,
March 2005, vol. III, pp. 73-76
[
Slides ]
Speaker
Localization using excitation source information in speech Vikas
C. Raykar, B.Yegnanarayana, S.
R. Mahadeva Prasanna, and Ramani Duraiswami, IEEE Transactions on
Speech and Audio Processing, Volume 13, Issue 5, Part 2, pp. 751-761,
Sep. 2005.
Extracting the frequencies of the pinna
spectral notches in measured head related impulse responses Vikas
C. Raykar, Ramani Duraiswami, and B. Yegnanarayana, The Journal of
the Acoustical Society of America, Volume 118, Issue 1, pp.
364-374, July 2005.
[A more detailed version available as CS-TR-4609]
Extracting the frequencies of the pinna spectral notches in measured head related impulse responses. Vikas C. Raykar, Ramani Duraiswami, and B. Yegnanarayana (presented at the 148th meeting of Acoustical Society of America, San Diego, California, November 2004) [Slides]
A study of pinna anthropometry and the spectral notch frequencies. Vikas C. Raykar, Ramani Duraiswami, and B. Yegnanarayana (presented at the 148th meeting of Acoustical Society of America, San Diego, California, November 2004) [Slides]
Providing Common Time and Space in
Distributed AV-Sensor Networks by Self-Calibration
R. Lienhart, I. Kozintsev, D. Budnikov, I. Chikalov, and V. C.
Raykar
in Intelligent Multimedia Processing
with Soft Computing
Position Calibration of Microphones and
Loudspeakers in Distributed Computing Platforms Vikas C. Raykar,
Igor Kozintsev, and Rainer Lienhart, IEEE Transactions on Speech and
Audio Processing, Volume 13, Issue 1, pp. 70-83, Jan. 2005.
Automatic
Position Calibration of
Multiple Microphones Vikas C. Raykar and Ramani Duraiswami, In
Proceedings of International Conference on Acoustics, Speech and Signal
Processing (ICASSP 2004), Montreal,
Canada, May 2004, vol. IV, pp. 69-72
[
Slides
]
Position Calibration of Audio
sensors and actuators in a distributed computing platform
Vikas C. Raykar, Igor Kozintsev and Rainer Lienhart
(ACM Multimedia 2003, Berkeley, CA, USA, November 2003, pp. 572-581)
(acceptance rate of 17%)
[
Slides ]
Self Localization of acoustic sensors
and actuators on distributed platforms Vikas C. Raykar,
Igor Kozintsev and Rainer Lienhart (ICCV 2003 International Workshop on
Multimedia Technologies in E-Learning and Collaboration, Nice, France,
October 2003)
[
Slides ]
Tracking a moving speaker using
excitation source information
Vikas C. Raykar, Ramani
Duraiswami, B.Yegnanarayana, and S. R. Mahadeva Prasanna, In
Proceedings of the 8th Eur. Conf. Speech Communication Technology
(Eurospeech 2003), Geneva, September 2003, pp. 69-72.
Extracting significant features from
the HRTF
Vikas C. Raykar, B.Yegnanarayana, R. Duraiswami, and L. Davis, In
9th International Conference on Auditory Display (ICAD 2003), Boston, July 2003, pp.
115-118.
Virtual
audio system customization using visual matching of ear parameters
D. Zotkin, R. Duraiswami, L.
Davis, A. Mohan, and V. Raykar, In Proceedings of the
16th Internationl Conference on Pattern Recognition (ICPR
2002), Quebec City, August 2002, Volume 3, pp.
1003-1006
Head Related Impulse Response
Interpolation for Dynamic
Spatialization T.V.Sreenivas, Vikas C. Raykar and
Ramesh Raman, Texas Instruments DSPS fest-2k, November
2000, Banglore, India.
Fast weighted summation of erfc functions. Vikas C. Raykar, R. Duraiswami, and B. Krishnapuram, CS-TR-4848, Department of computer science, University of Maryland, CollegePark. [abstract] [TR] [slides] [code] [bib]
Very fast optimal bandwidth selection for univariate kernel density estimation. Vikas C. Raykar and R. Duraiswami, CS-TR-4774, Department of computer science, University of Maryland, CollegePark. [abstract] [TR] [slides] [code] [bib]
Fast computation of sums of Gaussians in high dimensions. Vikas C. Raykar, C. Yang, R. Duraiswami, and N. Gumerov, CS-TR-4767, Department of computer science, University of Maryland, Collegepark. [abstract] [TR] [slides] [code] [bib]
Extracting frequencies of the pinna
spectral notches in measured head related impulse responses Vikas
C. Raykar, Ramani Duraiswami, and B. Yegnanarayana, University of
Maryland CollegePark, Department of Computer Science Technical
Report, CS-TR-4609, July 2004 (also published as
UMIACS-TR-2004-51).
Scalable machine learning for massive datasets: Fast summation algorithms Doctoral dissertation, Department of computer science, University of Maryland College Park, March 2007 [ Research Summary ] [ Thesis ] [ Slides ]
Position calibration of
acoustic sensors and actuators on distributed general purpose computing
platforms
Masters thesis, Department of
electrical engineering, University of Maryland College Park, December
2003