Browsing Computer Science and Automation (CSA) by thesis submitted date"2017"
Now showing items 21-33 of 33
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New Methods for Learning from Heterogeneous and Strategic Agents
(2018-05-21)1 Introduction In this doctoral thesis, we address several representative problems that arise in the context of learning from multiple heterogeneous agents. These problems are relevant to many modern applications such as ... -
New Techniques for Automatic Short Answer Grading
Assessing acquired knowledge by students is one of the key aspects of the pedagogical ecosystem. A significant part of a teacher’s time is spent towards grading responses of students to questions given in assignments and ... -
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 ... -
Optimization Algorithms for Deterministic, Stochastic and Reinforcement Learning Settings
(2018-05-30)Optimization is a very important field with diverse applications in physical, social and biological sciences and in various areas of engineering. It appears widely in ma-chine learning, information retrieval, regression, ... -
Program Analyses to Support Memory-saving Refactorings in Java Programs
Software commonly consumes unexpectedly high amounts of memory, frequently due to programming idioms that are used to make software more reliable, maintainable and understandable. In the case of modern object-oriented ... -
Program Repair by Automated Generation of Hints
Programming has become an important skill in today's technology-driven world. It is a complex activity because of which programmers make mistakes in their software. Student programmers make mistakes in their programs due ... -
Scalable Sprase Bayesian Nonparametric and Matrix Tri-factorization Models for Text Mining Applications
(2018-05-23)Hierarchical Bayesian Models and Matrix factorization methods provide an unsupervised way to learn latent components of data from the grouped or sequence data. For example, in document data, latent component corn-responds ... -
Stochastic approximation with set-valued maps and Markov noise: Theoretical foundations and applications
Stochastic approximation algorithms produce estimates of a desired solution using noisy real world data. Introduced by Robbins and Monro, in 1951, stochastic approximation techniques have been instrumental in the asymptotic ... -
Stochastic Newton Methods With Enhanced Hessian Estimation
(2018-05-22)Optimization problems involving uncertainties are common in a variety of engineering disciplines such as transportation systems, manufacturing, communication networks, healthcare and finance. The large number of input ... -
A Study of Thompson Sampling Approach for the Sleeping Multi-Armed Bandit Problem
(2018-05-29)The multi-armed bandit (MAB) problem provides a convenient abstraction for many online decision problems arising in modern applications including Internet display advertising, crowdsourcing, online procurement, smart grids, ... -
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, ... -
Towards a Charcterization of the Symmetries of the Nisan-Wigderson Polynomial Family
(2018-07-09)Understanding the structure and complexity of a polynomial family is a fundamental problem of arithmetic circuit complexity. There are various approaches like studying the lower bounds, which deals with nding the smallest ... -
Utilizing Worker Groups And Task Dependencies in Crowdsourcing
Crowdsourcing has emerged as a convenient mechanism to collect human judgments on a variety of tasks, ranging from document and image classification to scientific experimentation. However, in recent times crowdsourcing has ...