MVA

Labs and homeworks done during the Master Mathematics, Vision, Learning (MVA) at ENS Paris-Saclay.

First semester

Course	Homework
Convex Optimization	Convexity, Conjugate Function
	Duality
	LASSO
Deep Learning	Natural Language Processing
	Deep Q-learning
Graphs for Machine Learning	Spectral Clustering
	Semi-Supervised Learning
	Graph Neural Networks
Object Recognition and Computer Vision	Objects Matching, Image Retrieval
	Neural Networks
	Bird Classification Challenge
Probabilistic Graphical Models	Discrete Graphical Models, Linear Classification
	EM Algorithm, Ising Model and Loopy Belief Propagation
	Gibbs Sampling, Mean Field VB
Reinforcement Learning	Finite MDPs, Function Approximation
	Exploration in Linear Bandits and in Reinforcement Learning

Second semester

Course	Homework
Biostatistics	Treatment effect estimation, COVID-19
Deep Learning in Practice	Hyperparameters tuning
	Grad-CAM
	Graph Neural Networks
	Active Learning
	Rossler Attractor
	Generative Models
Kernel Methods	Kernels, Optimization
Multiscale models and CNNs	Paris Fire Brigade Challenge
Neurosciences	Predictive Coding
Sequential Learning	Game Theory, Sleeping Experts