## Walid Krichene## Course work## Control and Optimization## EE227C: Convex Optimization and Approximation (Spring 2014, Berkeley)Project on Convex optimization in game theory. ## EE222A: Nonlinear Systems Theory (Fall 2013, Berkeley)Taught by Professor Murat Arcak. ## EE227A: Convex Optimization (Spring 2012, Berkeley)Convex sets and functions. Linear programming, SOCP and SDP. Weak and strong duality. Optimality conditions and sensitivity analysis. ## EE221A: Linear Systems Theory (Fall 2011, Berkeley)Linear algebra: eigenspaces, SVD, Jordan form, spectral mapping theorem. Least sqaures problems, pseudo-inverse. ## Discrete Event Systems (Spring 2010, Mines Paristech)Introduction to max-plus algebras. ## Introduction to Non Linear Control and applications to Robotics (Spring 2010, Mines Paristech)Dynamical systems, Lyapunov stability. ## Signal Processing and telecommunication (Spring 2010, Mines Paristech)Sampling. DFT and FFT. Aliasing, Nyquist-Shannon theorem. Impulse response and Finite Response filters. ## Introduction to optimization (Spring 2009, Mines Paristech, audited)Unconstrained optimization. Numerical methods, line search, convergence, Newton method, conjugate gradient. ## Introduction to Control Theory (Fall 2008, Caltech)Stability, Lyapunov, controllability and state space feedback. Linear systems and discrete time systems. ## Dynamical Systems and Control (Spring 2008, Mines Paristech)Introduction to linear control. Stability, robustness, perturbations. ## Algorihtms and Computer Science## Principle of reactive programming (Coursera - EPFL, Fall 2013)Introduction to ScalaCheck. Taught by Erik Meijer, Martin Odersky and Roland Kuhn. ## Combinatorial Algorithms and Data Structures CS270 (Spring 2013, Berkeley)Experts’ algorithm, applications to min-max for zero-sum two player games and Boosting. Taught by Professor Satish Rao. ## Principles of functional programming (Coursera - EPFL, Spring 2013)Introduction to functional programming and the Scala language. Taught by Professor Martin Odersky. certificate ## Algorithmic Game Theory (Fall 2011, Berkeley)Nash equilibria. 2 player zero-sum games, min-max solutions and linear programming. Taught by Professor Christos Papadimitriou. ## Distributed applications (Spring 2010, Mines Paristech)Low level and high level network protocols (Ethernet, TCP, UDP, HTTP). ## Computational Steering in Science and Engineering (November 2009, Munich Technical University)Athens intensive course (exchange program) ## Information Systems (Spring 2009, Mines Paristech)Relational databases theory. Design and implementation of databases. ## Information and Complexity (Fall 2008, Caltech, audited)Entropy and mutual information, symbol coding, unique decodability, Huffman coding, rate-distortion. ## Machine Learning and Statistics## Statistical Learning Theory CS281/STAT241 (Fall 2012, Berkeley)Graphical Models, inference and statistical estimation. Markov properties, elimination. Junction tree algorithm. ## Random Processes in Systems EE226 (Fall 2011, Berkeley)Probability theory, discrete time Markov chains, ergodicity, queuing systems, reversibility. ## Practical Machine Learning (Spring 2009, Mines Paristech)Neural Networks and back propagation. ## Statistics (Spring 2009, Mines Paristech)Statistical modeling, estimators, confidence tests. ## Learning Systems (Fall 2008, Caltech)The learning problem. Model complexity and over-fitting. VC dimension, bias-variance tradeoff, and regularization. ## Probability Theory (Spring 2008, Mines Paristech)Random variables, moments, conditional laws, transformations, convergence. ## Mathematics## Probability Theory MATH 218A / STATS 205A - Fall 2013, BerkeleyTaught by Professor David Aldous ## Topology and Analysis MATH 202A/B, Fall 2012 - Spring 2013, Berkeley.Taught by Professor Michael Christ. ## Cryptography and Number Theory (Fall 2009, Mines Paristech)Number theory: arithmetics, Euler function, zeta function, Lucas theorem, prime number distribution. ## Distribution theory (Fall 2009, Mines Paristech)Distribution spaces. Fourier transform, convolution. |