Browsing Computer Science and Automation (CSA) by Advisor "Bhattacharyya, Chiranjib"
Now showing items 1-16 of 16
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Algorithms for Multilingual IR in Low Resource Languages using Weakly Aligned Corpora
Multilingual information retrieval (MLIR) methods generally rely on linguistic resources such as dictionaries, parallel corpora, etc., to overcome the language barrier. For low resource languages without these resources, ... -
Battle of Bandits: Online Learning from Subsetwise Preferences and Other Structured Feedback
The elicitation and aggregation of preferences is often the key to making better decisions. Be it a perfume company wanting to relaunch their 5 most popular fragrances, a movie recommender system trying to rank the most ... -
Bayesian Nonparametric Modeling of Temporal Coherence for Entity-Driven Video Analytics
(2018-05-14)In recent times there has been an explosion of online user-generated video content. This has generated significant research interest in video analytics. Human users understand videos based on high-level semantic ... -
Boolean Functional Synthesis using Gated Continuous Logic Networks
Boolean Functional Synthesis (BFS) is a well-known challenging problem in the domain of automated program synthesis from logical specifications. This problem aims to synthesize a Boolean function that is correct-by-construction ... -
Computational Protein Structure Analysis : Kernel And Spectral Methods
(2010-08-24)The focus of this thesis is to develop computational techniques for analysis of protein structures. We model protein structures as points in 3-dimensional space which in turn are modeled as weighted graphs. The problem of ... -
Discovery Of Application Workloads From Network File Traces
(2011-05-19)An understanding of Input/Output data access patterns of applications is useful in several situations. First, gaining an insight into what applications are doing with their data at a semantic level helps in designing ... -
Hard Drive Failure Prediction : A Rule Based Approach
(2011-07-12)The ability to accurately predict an impending hard disk failure is important for reliable storage system design. The facility provided by most hard drive manufacturers, called S.M.A.R.T. (self-monitoring, analysis and ... -
Learning Algorithms Using Chance-Constrained Programs
(2010-07-08)This thesis explores Chance-Constrained Programming (CCP) in the context of learning. It is shown that chance-constraint approaches lead to improved algorithms for three important learning problems — classification with ... -
Learning Robust Support Vector Machine Classifiers With Uncertain Observations
(2015-08-19)The central theme of the thesis is to study linear and non linear SVM formulations in the presence of uncertain observations. The main contribution of this thesis is to derive robust classfiers from partial knowledge of ... -
Learning to Adapt Policies for uSD card
Machine Learning(ML) for Systems is a new and promising research area where performance of computer systems is optimized using machine learning methods. ML for Systems has outperformed traditional heuristics methods in ... -
Near-Duplicate Detection Using Instance Level Constraints
(2011-08-09)For the task of near-duplicate document detection, comparison approaches based on bag-of-words used in information retrieval community are not sufficiently accurate. This work presents novel approach when instance-level ... -
Non-Parametric Clustering of Multivariate Count Data
(2018-05-23)The focus of this thesis is models for non-parametric clustering of multivariate count data. While there has been significant work in Bayesian non-parametric modelling in the last decade, in the context of mixture models ... -
Novel First-order Algorithms for Non-smooth Optimization Problems in Machine Learning
This thesis is devoted to designing efficient optimization algorithms for machine learning (ML) problems where the underlying objective function to be optimized is convex but not necessarily differentiable. Such non-smooth ... -
Provable Methods for Non-negative Matrix Factorization
(2017-10-31)Nonnegative matrix factorization (NMF) is an important data-analysis problem which concerns factoring a given d n matrix A with nonnegative entries into matrices B and C where B and C are d k and k n with nonnegative ... -
Structured Regularization Through Convex Relaxations Of Discrete Penalties
Motivation. Empirical risk minimization(ERM) is a popular framework for learning predictive models from data, which has been used in various domains such as computer vision, text processing, bioinformatics, neuro-biology, ... -
Supervised Classification of Missense Mutations as Pathogenic or Tolerated using Ensemble Learning Methods
(2018-07-09)Missense mutations account for more than 50% of the mutations known to be involved in human inherited diseases. Missense classification is a challenging task that involves sequencing of the genome, identifying the variations, ...