Randomized Algorithms for Large scale SVMs (2009)
Jethava, Vinay, Suresh, Krishnan, Bhattacharyya, Chiranjib, Hariharan, Ramesh
We propose a randomized algorithm for training Support vector machines(SVMs) on large datasets. By using ideas from Random projections we show that the combinatorial dimension of SVMs is $O({log} n)$...
Bhadra, Sahely, Bhattacharyya, Chiranjib, Chandra, Nagasuma R, Mian, I Saira
Abstract Background A genetic network can be represented as a directed graph in which a node corresponds to a gene and a directed edge specifies the direction of influence of one gene on another. The...
Simultaneous Feature Selection and Classification for Relevance Feedback in Image Retrieval (2009)
Reshma Prasanna, K. R. Ramakrishnan, Chiranjib Bhattacharyya
Abstract — In image retrieval, relevance feedback uses information, obtained interactively from the user, to understand the user’s perceptions of a query image and to improve retrieval accuracy....
A Randomized Algorithm for Large Scale Support Vector Learning (2009)
Krishnan S, Chiranjib Bhattacharyya, Ramesh Hariharan, Strand Genomics
We propose a randomized algorithm for large scale SVM learning which solves the problem by iterating over random subsets of the data. Crucial to the algorithm for scalability is the size of the...
Focused Crawling with Scalable Ordinal Regression Solvers Overview (2009)
Chiranjib Bhattacharyya, M N Murty
• Propose a clustering based, scalable, OR formulation: – Classifies data clusters, instead of data points – Instance of SOCP with one SOC constraint. • Develop a fast solver, for proposed OR...
Efficient Algorithms for Intrusion Detection (2009)
Niranjan K. Boora, Chiranjib Bhattacharyya, K. Gopinath
Abstract. Detecting user to root attacks is an important intrusion detection task. This paper uses a mix of spectrum kernels and probabilistic suffix trees, as a possible solution for detecting such...
Bhadra, Sahely, Bhattacharyya, Chiranjib, Chandra, Nagasuma R, Mian, I Saira
Background: A genetic network can be represented as a directed graph in which a node corresponds to a gene and a directed edge specifies the direction of influence of one gene on another. The...
RAPID: Resource of Asian Primary Immunodeficiency Diseases (2009)
Keerthikumar, Shivakumar, Raju, Rajesh, Kandasamy, Kumaran, Hijikata, Atsushi, Ramabadran, Subhashri, Balakrishnan, Lavanya, ...
Availability of a freely accessible, dynamic and integrated database for primary immunodeficiency diseases (PID) is important both for researchers as well as clinicians. To build a PID informational...
RAPID: Resource of Asian Primary Immunodeficiency Diseases (2009)
Keerthikumar, Shivakumar, Raju, Rajesh, Kandasamy, Kumaran, Hijikata, Atsushi, Ramabadran, Subhashri, Balakrishnan, Lavanya, ...
Availability of a freely accessible, dynamic and integrated database for primary immunodeficiency diseases (PID) is important both for researchers as well as clinicians. To build a PID informational...
Interval Data Classification under Partial Information: A Chance-Constraint Approach (2009)
Bhadra, Sahely, Nath, J Saketha, Ben-Tal, Aharou, Bhattacharyya, Chiranjib
This paper presents a Chance-constraint Programming approach for constructing maximum-margin classifiers which are robust to interval-valued uncertainty in training examples. The methodology ensures...
Keerthikumar, Shivakumar, Bhadra, Sahely, Kandasamy, Kumaran, Raju, Rajesh, Ramachandra, Y.L., Bhattacharyya, Chiranjib, ...
Screening and early identification of primary immunodeficiency disease (PID) genes is a major challenge for physicians. Many resources have catalogued molecular alterations in known PID genes along...
Mehul Parsana, Chiranjib Bhattacharyya, Sourangshu Bhattacharya, K. R. Ramakrishnan
This paper introduces kernels on attributed pointsets, which are sets of vectors embedded in an euclidean space. The embedding gives the notion of neighborhood, which is used to define positive...
Second order cone programming formulations for feature selection (2008)
This paper addresses the issue of feature selection for linear classifiers given the moments of the class conditional densities. The problem is posed as finding a minimal set of features such that...
Mehul Parsana, Chiranjib Bhattacharyya, Sourangshu Bhattacharya, K. R. Ramakrishnan
This paper introduces kernels on attributed pointsets, which are sets of vectors embedded in an euclidean space. The embedding gives the notion of neighborhood, which is used to define positive...
Structural Alignment based Kernels for Protein Structure Classification (2008)
Sourangshu Bhattacharya, Chiranjib Bhattacharyya, Nagasuma Chandra
Structural alignments are the most widely used tools for comparing proteins with low sequence similarity. The main contribution of this paper is to derive various kernels on proteins from structural...
Focused Crawling with Scalable Ordinal Regression Solvers (2008)
Rashmin Babaria, J. Saketha Nath, Krishnan S, Sivaramakrishnan K R, Chiranjib Bhattacharyya
In this paper we propose a novel, scalable, clustering based Ordinal Regression formulation, which is an instance of a Second Order Cone Program (SOCP) with one Second Order Cone (SOC) constraint....
Mean-field methods for a special class of Belief Networks (2007)
Chiranjib Bhattacharyya, S. Sathiya Keerthi
The chief aim of this paper is to propose mean-field approximations for a broad class of Belief networks, of which sigmoid and noisy-or networks can be seen as special cases. The approximations are...
Comparison of protein structures by growing neighborhood alignments (2007)
Bhattacharya, Sourangshu, Bhattacharyya, Chiranjib, Chandra, Nagasuma R
Abstract Background Design of protein structure comparison algorithm is an important research issue, having far reaching implications. In this article, we describe a protein structure comparison...
Comparison of protein structures by growing neighborhood alignments (2007)
Bhattacharya, Sourangshu, Bhattacharyya, Chiranjib, Chandra, Nagasuma R
Design of protein structure comparison algorithm is an important research issue, having far reaching implications. In this article, we describe a protein structure comparison scheme, which is capable...
Comparison of protein structures by growing neighborhood alignments (2007)
Bhattacharya, Sourangshu, Bhattacharyya, Chiranjib, Chandra, Nagasuma R
Design of protein structure comparison algorithm is an important research issue, having far reaching implications. In this article, we describe a protein structure comparison scheme, which is capable...
Learning Algorithms using Chance-Constrained Programs (2007)
Nath Jagarlapudi, J. Saketha Nath, Chiranjib Bhattacharyya, M. Narasimha, Murty Clustering
I would like to express sincere gratitude and thanks to my adviser, Dr. Chiranjib Bhat-tacharyya. With his interesting thoughts and ideas, inspiring ideals and friendly nature, he made sure I was...
Projections for fast protein structure retrieval (2006)
Bhattacharya, Sourangshu, Bhattacharyya, Chiranjib, Chandra, Nagasuma R
Abstract Background In recent times, there has been an exponential rise in the number of protein structures in databases e.g. PDB. So, design of fast algorithms capable of querying such databases is...
Projections for fast protein structure retrieval (2006)
Bhattacharya, Sourangshu, Bhattacharyya, Chiranjib, Chandra, Nagasuma R
Background: In recent times, there has been an exponential rise in the number of protein structures in databases e. g. PDB. So, design of fast algorithms capable of querying such databases is...
Projections for fast protein structure retrieval (2006)
Bhattacharya, Sourangshu, Bhattacharyya, Chiranjib, Chandra, Nagasuma R
Background: In recent times, there has been an exponential rise in the number of protein structures in databases e. g. PDB. So, design of fast algorithms capable of querying such databases is...
Second Order Cone Programming Approaches for Handling Missing and Uncertain Data (2006)
Shivaswamy, Pannagadatta K, Bhattacharyya, Chiranjib, Smola, Alexander J
We propose a novel second order cone programming formulation for designing robust classifiers which can handle uncertainty in observations. Similar formulations are also derived for designing...
Second Order Cone Programming Approaches for Handling Missing and Uncertain Data (2006)
Shivaswamy, Pannagadatta K, Bhattacharyya, Chiranjib, Smola, Alexander J
We propose a novel second order cone programming formulation for designing robust classifiers which can handle uncertainty in observations. Similar formulations are also derived for designing...
For Handling Missing, Pannagadatta K. Shivaswamy, Chiranjib Bhattacharyya, Alexander J. Smola, P. Bennett, Emilio Parrado-hernández
We propose a novel second order cone programming formulation for designing robust classifiers which can handle uncertainty in observations. Similar formulations are also derived for designing...
Mathematical Programming for Missing Data (2004)
Bhattacharyya, Chiranjib, Pannagadatta, K.S., Smola, Alex
We propose a mathematical programming method to deal with uncertainty in the observations of a classification problem. This means that we can deal with situations where instead of a sample $(\xb_i,...
Second Order Cone Programming Formulations for Feature Selection (2004)
This paper addresses the issue of feature selection for linear classifiers given the moments of the class conditional densities. The problem is posed as finding a minimal set of features such that...
Robust Classification of noisy data using Second Order Cone Programming approach (2004)
Assuming an ellipsoidal model of uncertainty a robust formulation for classifying noisy data is presented. The formulation is a convex optimization problem, in par- ticular it is a instance of Second...
Second Order Cone Programming Formulations for Feature Selection (2004)
This paper addresses the issue of feature selection for linear classifiers given the moments of the class conditional densities. The problem is posed as finding a minimal set of features such that...
A second order cone programming formulation for classifying missing data (2004)
Bhattacharyya, Chiranjib, Pannagadatta, K.S., Smola, Alex
We propose a convex optimization based strategy to deal with uncertainty in the observations of a classification problem. We assume that instead of a sample (xi , yi ) a distribution over (xi , yi )...
Efficient Algorithms for Intrusion Detection (2004)
Boora, Niranjan K, Bhattacharyya, Chiranjib, Gopinath, K
Detecting user to root attacks is an important intrusion detection task. This paper uses a mix of spectrum kernels and probabilistic suffix trees as a possible solution for detecting such intrusions...
Robust Classification of noisy data using Second Order Cone Programming approach (2004)
Assuming an ellipsoidal model of uncertainty a robust formulation for classifying noisy data is presented. The formulation is a convex optimization problem, in par- ticular it is a instance of Second...
Efficient Algorithms for Intrusion Detection (2004)
Boora, Niranjan K, Bhattacharyya, Chiranjib, Gopinath, K
Detecting user to root attacks is an important intrusion detection task. This paper uses a mix of spectrum kernels and probabilistic suffix trees as a possible solution for detecting such intrusions...
Simultaneous Feature Selection and Classification for Relevance Feedback in Image Retrieval (2003)
Prasanna, Reshma, Ramakrishnan, KR, Bhattacharyya, Chiranjib
In image retrieval, relevance feedback uses information, obtained interactively from the user, to understand the user's perceptions of a query image and to improve retrieval accuracy. We propose...
Simultaneous Feature Selection and Classification for Relevance Feedback in Image Retrieval (2003)
Prasanna, Reshma, Ramakrishnan, KR, Bhattacharyya, Chiranjib
In image retrieval, relevance feedback uses information, obtained interactively from the user, to understand the user's perceptions of a query image and to improve retrieval accuracy. We propose...
Minimax probability machine (2002)
Laurent El Ghaoui, Chiranjib Bhattacharyya, Michael I. Jordan
When constructing a classier, the probability of correct classi-cation of future data points should be maximized. In the current paper this desideratum is translated in a very direct way into an...
Minimax probability machine (2002)
Laurent El Ghaoui, Chiranjib Bhattacharyya, Michael I. Jordan
When constructing a classifier, the probability of correct classification of future data points should be maximized. In the current paper this desideratum is translated in a very direct way into an...
A Robust Minimax Approach to Classification (2002)
Laurent E Ghaoui, Chiranjib Bhattacharyya, Michael I. Jordan
When constructing a classifier, the probability of correct classification of future data points should be maximized. We consider a binary classification problem where the mean and covariance matrix...
A robust minimax approach to classification (2002)
Laurent El Ghaoui, Chiranjib Bhattacharyya, Michael I. Jordan, Bernhard Schölkopf
When constructing a classifier, the probability of correct classification of future data points should be maximized. We consider a binary classification problem where the mean and covariance matrix...
A robust minimax approach to classification (2002)
Laurent El Ghaoui, Chiranjib Bhattacharyya, Michael I. Jordan, Bernhard Schölkopf
When constructing a classifier, the probability of correct classification of future data points should be maximized. We consider a binary classification problem where the mean and covariance matrix...
A robust minimax approach to classification (2002)
Laurent El Ghaoui, Laurent El Ghaoui, Chiranjib Bhattacharyya, Chiranjib Bhattacharyya
When constructing a classifier, the probability of correct classification of future data points should be maximized. We consider a binary classification problem where the mean and covariance matrix...
Chiranjib Bhattacharyya, Pannagadatta K. S, Alexander J. Smola
We propose a convex optimization based strategy to deal with uncertainty in the observations of a classification problem. We assume that instead of a sample (xi, yi) a distribution over (xi, yi) is...
Chiranjib Bhattacharyya, Pannagadatta K. S, Alexander J. Smola
We propose a mathematical programming method to deal with uncertainty in the observations of a classification problem. This means that we can deal with situations where instead of a sample (xi, yi)...
Projections for fast protein structure retrieval
Bhattacharya, Sourangshu, Bhattacharyya, Chiranjib, Chandra, Nagasuma R
Comparison of protein structures by growing neighborhood alignments
Bhattacharya, Sourangshu, Bhattacharyya, Chiranjib, Chandra, Nagasuma R
RAPID: Resource of Asian Primary Immunodeficiency Diseases
Keerthikumar, Shivakumar, Raju, Rajesh, Kandasamy, Kumaran, Hijikata, Atsushi, Ramabadran, Subhashri, Balakrishnan, Lavanya, ...
Availability of a freely accessible, dynamic and integrated database for primary immunodeficiency diseases (PID) is important both for researchers as well as clinicians. To build a PID informational...
Keerthikumar, Shivakumar, Bhadra, Sahely, Kandasamy, Kumaran, Raju, Rajesh, Ramachandra, Y.L., Bhattacharyya, Chiranjib, ...
Screening and early identification of primary immunodeficiency disease (PID) genes is a major challenge for physicians. Many resources have catalogued molecular alterations in known PID genes along...