• Computational Protein Structure Analysis : Kernel And Spectral Methods 

      Bhattacharya, Sourangshu (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 

      Yadwadkar, Neeraja (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 

      Agrawal, Vipul (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 

      Jagarlapudi, Saketha Nath (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 

      Bhadra, Sahely (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 ...
    • Near-Duplicate Detection Using Instance Level Constraints 

      Patel, Vishal (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 

      Tekumalla, Lavanya Sita (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 ...
    • Provable Methods for Non-negative Matrix Factorization 

      Pani, Jagdeep (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 ...
    • Supervised Classification of Missense Mutations as Pathogenic or Tolerated using Ensemble Learning Methods 

      Balasubramanyam, Rashmi (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, ...