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Shai shalev schwartz thesis proposal

Shai shalev schwartz thesis proposal Sampling Based Approach to Facial

Research Interests. Machine Learning. Record Learning Theory, Online Learning, Optimization, Empirical Process Theory, Concentration Inequalities, Game Theory

  • On Equivalence of Martingale Tail Bounds and Deterministic Regret Inequalities
    Alexander Rakhlin, Karthik Sridharan
    [ArXiv]

  • On Consecutive Probability Assignment with Binary Alphabets and enormous Classes of Experts
    Alexander Rakhlin, Karthik Sridharan
    [pdf]

  • Online Nonparametric Regression with General Loss Functions
    Alexander Rakhlin, Karthik Sridharan
    [Arxiv]

  • On Convex Optimization, Fat Shattering and Learning
    Nathan Srebro, Karthik Sridharan
    [pdf]

  • BISTRO: A Competent Relaxation-Based Way of Contextual Bandits
    Alexander Rakhlin, Karthik Sridharan
    ICML 2016, [ArXiv]

  • Differentially Private Causal Inference
    Matt Kusner, Yu Sun, Karthik Sridharan. Kilian Weinberger
    AISTATS 2016

  • Adaptive Online Learning
    Dylan Promote, Alexander Rakhlin, Karthik Sridharan
    NIPS 2015, [arxiv]

  • Hierarchies of Relaxations for Online Conjecture Issues with Evolving Constraints
    Alexander Rakhlin, Karthik Sridharan
    COLT 2015, [arxiv]

  • Learning with Square Loss: Localization through Offset Rademacher Complexity
    Tengyuan Liang, Alexander Rakhlin, Karthik Sridharan
    COLT 2015, [arxiv]

  • Online Optimization. Rivaling Dynamic Comparators
    Ali Jadbabaie, Alexander Rakhlin, Shahin Shshrampour, Karthik Sridharan
    AISTATS 2015, [pdf]

  • Online Nonparametric Regression
    Alexander Rakhlin, Karthik Sridharan
    COLT 2014 [pdf]

  • On Martingale Extensions of Vapnik-Chervonenkis Theory with Applications to Online Learning
    Alexander Rakhlin, Karthik Sridharan
    To look in Book Chapter. Festschrift in recognition of the. Chervonenkis. [pdf]

  • On Semi-Probabilistic Universal Conjecture
    Alexander Rakhlin, Karthik Sridharan
    Proceedings of IEEE Information Theory Workshop, 2013. Asked paper [pdf]

  • Optimization, Learning, and Games with Foreseeable Sequences
    Alexander Rakhlin, Karthik Sridharan
    NIPS 2013 [pdf]

  • Rivaling Strategies
    Wei Han, Alexander Rakhlin, Karthik Sridharan
    COLT 2013 [pdf]

  • Online Learning with Foreseeable Sequences
    Alexander Rakhlin, Karthik Sridharan
    COLT 2013 [pdf]. [Arxiv version]

  • Localization and Adaptation in Online Learning (full dental presentation)
    Alexander Rakhlin, Ohad Shamir, Karthik Sridharan
    AISTATS 2013

  • Relax and Randomize: From Value to Algorithms (full dental presentation)
    Alexander Rakhlin, Ohad Shamir, Karthik Sridharan
    NIPS 2012 [pdf]

  • Making Stochastic Gradient Descent Optimal for Strongly Convex Problems
    Alexander Rakhlin, Ohad Shamir, Karthik Sridharan
    ICML 2012 [Arxiv Version]

  • Minimizing The Misclassification Error Rate Utilizing a Surrogate Convex Loss
    Shai Ben-David, David Loker, Nathan Srebro, Karthik Sridharan
    ICML 2012 [pdf]

  • Around the Universality of internet Mirror Descent
    Nathan Srebro, Karthik Sridharan. Ambuj Tewari
    NIPS 2011 [Arxiv Version]

  • Better Small-Batch Algorithms via Faster Gradient Methods
    Andrew Cotter, Ohad Shamir. Nathan Srebro, Karthik Sridharan
    NIPS 2011 [Arxiv Version]

  • Online Learning: Stochastic and Restricted Adversaries
    Alexander Rakhlin, Karthik Sridharan. Ambuj Tewari
    NIPS 2011 [pdf] [Arxiv Version]

  • Online Learning: Beyond Regret (best paper award)
    Alexander Rakhlin, Karthik Sridharan. Ambuj Tewari
    COLT 2011, [pdf] [Arxiv Version]

  • Complexity-Based Method of Calibration with Checking Rules
    Dean Promote, Alexander Rakhlin, Karthik Sridharan. Ambuj Tewari
    COLT 2011, [pdf]

  • Online Learning: Random Averages, Combinatorial Parameters and Learnability (full dental presentation)
    Alexander Rakhlin, Karthik Sridharan. Ambuj Tewari
    NIPS 2010 [pdf] [Arxiv Version]

  • Level of smoothness, Low-Noise and Fast Rates
    Nathan Srebro, Karthik Sridharan. Ambuj Tewari
    NIPS 2010 [pdf] [Arxiv version]

  • Robust Selective Sampling from Single and Multiple Teachers
    Ofer Dekel, Claudio Gentile, Karthik Sridharan
    COLT 2010 [pdf]

  • Convex Games in Banach Spaces
    Karthik Sridharan. Ambuj Tewari
    COLT 2010 [pdf]

  • Learning Kernel-Based Halfspaces using the Zero-One Loss (best paper award)
    Shai Shalev-Shwartz, Ohad Shamir, Karthik Sridharan
    COLT 2010 [pdf]. A shorter version presented in the best paper track IJCAI 2011 [pdf]

  • Learning exponential families in high-dimensions: Strong convexity and sparsity
    Sham Kakade, Ohad Shamir, Karthik Sridharan. Ambuj Tewari
    AISTATS 2010 [Arxiv version]

  • The Complexness of Incorrectly Learning Large Margin Halfspaces
    Shai Shalev-Shwartz, Ohad Shamir, Karthik Sridharan
    Open Problems, COLT 2009 [pdf]

  • Learnability and Stability within the General Learning Setting
    Shai Shalev-Shwartz, Ohad Shamir, Nathan Srebro, Karthik Sridharan
    COLT 2009 [pdf]

  • Stochastic Convex Optimization
    Shai Shalev-Shwartz, Ohad Shamir, Nathan Srebro, Karthik Sridharan
    COLT 2009 [pdf]

  • Multi-View Clustering via Canonical Correlation Analysis
    Kamalika Chaudhuri, Sham Kakade, Karen Livescu, Karthik Sridharan
    ICML 2009 [pdf]

  • Around the Complexity of Straight line Conjecture: Risk Bounds, Margin Bounds and Regularization
    Sham Kakade, Karthik Sridharan. Ambuj Tewari
    NIPS 2008 [pdf]

  • Fast Rates for Regularized Objectives
    Shai Shalev-Shwartz, Nathan Srebro, Karthik Sridharan
    NIPS 2008 [pdf]

  • Information Theoretic Framework for Multi-view Learning
    Karthik Sridharan. Sham M. Kakade
    21st Annual Conference on Learning Theory (COLT 2008) [pdf]

  • Competitive Mixtures of straightforward Neurons
    Karthik Sridharan. Matthew J Beal, Venu Govindaraju
    ICPR’06 [pdf]

  • Identifying handwritten text in mixed documents
    Faisal Farooq, Karthik Sridharan. Venu Govindaraju
    ICPR’06

  • Classification of Machine Print and Handwritten Arabic Documents
    Karthik Sridharan. Faisal Farooq, Venu Govindaraju
    (SDIUT 2005, pp. 89-94.)

  • A Sampling Based Method of Facial Feature Extraction IEEE link
    Karthik Sridharan. Venu Govindaraju
    (IEEE AUTOID 2005. Best Paper Award – Second Prize, pp.51-56)

  • A Probabilistic Method of Semantic Face Retrieval springer link
    Karthik Sridharan. Sankalp Nayak, Sharat Chikkerur, Venu Govindaraju
    (AVBPA 2005, pp.977-986.)

  • An Engaged Migration Model for Self-adaptive Genetic Algorithms springer link
    K.G. Srinivasa, Karthik Sridharan. P. Deepa Shenoy, Venugopal K.R. L.M. Patnaik
    (Proceedings of sixth Worldwide Conference on Intelligent Data Engineering and automatic Learning (IDEAL 05),
    Springer Verlag, LNCS, This summer sixth – ninth 2005, Queensland, Australia, pp. 555-562.)

  • A Highly Effective Content-Based Image Retrieval System Using STI Features and Relevance Feedback
    K.G. Srinivasa, Karthik Sridharan. P. Deepa Shenoy, Venugopal K.R. L.M. Patnaik
    (KBCS-2004, Fifth Worldwide Conference On Understanding Based Personal Computers,
    Hyderabad, India, December 19-22, 2004, pp. 290 – 301.)

  • EASOM: A Competent Soft Computing Way of Predicting the proportion Values ACTA press link
    K.G. Srinivasa, Karthik Sridharan. P. Deepa Shenoy, Venugopal K.R. L.M. Patnaik
    (Proceedings of IASTED Worldwide Conference on Artificial Intelligence and Applications (AIA 2004), ISSN: 1027-2666,
    Austria, Innsburg, February 16 – 18, 2004, pp. 264-269.)

  • Empirical Entropy, Minimax Regret and Minimax Risk
    Alexander Rakhlin, Karthik Sridharan. Alexandre Tsybakov
    Bernoulli Journal, 2014 (to look) [pdf]

  • Online Learning via Consecutive Complexities
    Alexander Rakhlin, Karthik Sridharan. Ambuj Tewari
    Journal of Machine Learning Research, 2014 (to look)

  • Consecutive Complexities and Uniform Martingale Laws and regulations of huge Figures
    Alexander Rakhlin, Karthik Sridharan. Ambuj Tewari
    Probability Theory and Related Fields, 2014, to look [pdf]

  • Selective Sampling and Active Gaining knowledge from Single and Multiple Teachers
    Ofer Dekel, Claudio Gentile, Karthik Sridharan
    Journal of Machine Learning Research, 2012 [pdf]

  • Learning Kernel Based Halfspaces using the -1 Loss
    Shai Shalev-Shwartz, Ohad Shamir, Karthik Sridharan
    SIAM Journal on Computing, 40(6):1623-1646, 2011 [pdf]

  • Learnability, Stability and Uniform Convergence
    Shai Shalev-Shwartz, Ohad Shamir, Nathan Srebro, Karthik Sridharan
    Journal of Machine Learning Research, 11(March):2635-2670, 2010 [pdf]

  • A Neural Network based CBIR System using STI Features and Relevance Feedback
    K.G. Srinivasa, Karthik Sridharan. P. Deepa Shenoy, Venugopal K.R. L.M. Patnaik
    Worldwide Journal on Intelligent Data Analysis, Volume 10, Number Two, 2006, IOS Press.

  • Doctorate Thesis. Gaining knowledge from an Optimization Point of view
    Karthik Sridharan Consultant. Nati Srebro
    Thesis Commitee. David McAllester, Arkadi Nemirovski, Alexander Razborov, Nathan Srebro
    Toyota Technological Institute at Chicago
    [pdf]

  • Master’s Thesis. Semantic Face Retrieval
    Karthik Sridharan
    Consultant. Venu Govindaraju
    Information Technology, SUNY Zoysia, 2006
    [pdf]

    E. Lecture Notes

  • Record Learning Theory and Consecutive Conjecture
    Alexander Rakhlin, Karthik Sridharan
    STAT 298, Lecture Notes [pdf]

  • A Light Summary of Concentration Inequalities
    Karthik Sridharan
    (Theorems and proofs of the couple of concentration inequalities) – [pdf] [ps] [dvi] [gzipped]

  • Fast Convergence Rates for Excess Regularized Risk with Application to SVM
    Karthik Sridharan
    [pdf]

  • Note on Refined Dudley Integral Covering Number Bound
    Nathan Srebro, Karthik Sridharan
    [pdf]

    G. National Conferences in India

  • A Manuscript Neural Network Method for Face Recognition and Recognition
    Karthik Sridharan
    (Top rated paper at Youthful IT Professional Award 2003, south regional laptop or computer Society asia, Bangalore chapter.)

  • A Counterpropagation Neural Network for Face Recognition and Recognition
    Karthik Sridharan. Jibi Abraham
    (SPIN 2003 national conference, Bangalore.)

  • Semantic Face Retrieval System

    The descriptions that individuals provide about human faces are frequently verbal anyway like, “blonde haired person” or “person with lengthy face”. The work involves instantly removing such semantic descriptions of faces in the image database and performing query in regards to a particular face using verbal descriptions more effective. We presently are utilizing Pruning of images according to description results in lack of the best images because of mistakes through the automated retrieval system or even the user. Hence we use Bayesian Learning for that query and retrieval part.

  • EM Based Probabilistic Neural Network for Supervised Learning

  • AROMA – A Recursive Optimization method using Multi-resolution Analysis

  • Guitar Recognition using Gaussian Mixture Model

    According to features such as the spectogram, psd, the LP co-efficients of the music wave file, a combination of gaussians may be used to model the extracted features and therefore recognize the instrument playing the bit of music. The work was transported in MATLAB and it was my final year undergraduate project.

  • Face Recognition and Recognition using Neural Network

    A Conuterpropagation neural network was utilized for face recognition and recognition in 2d images. The neural network was modeled so that just by altering the supervised area of the counter propagation network, face recognition might be done with similar network educated to do face recognition. It was my 3rd year (sixth sem) undergraduate project.


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    Shai shalev schwartz thesis proposal The neural network was modeled



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