**SPEAKERS**

# Speakers (Monday-Wednesday)

#### Francis BACH

Senior Researcher – INRIA

Adjunct Professor – ENS

Title: **Optimization for large-scale machine learning.**

#### Danielle BELGRAVE

Researcher – Microsoft Research, Cambridge, UK

Title: **Advances and challenges in machine learning for personalised healthcare.**

#### David COHEN

Professor – APHP Hôpital La Pitié Salpêtrière

Title: **AI and computational approaches: Implications for developmental psychopathology.**

#### Stéphane MALLAT

Professor – Collège de France, ENS

**Opening of the public morning session **

Title: **Mathematical mysteries of deep neural networks.**

#### Rada MIHALCEA

Professor – University of Michigan

Title: **Computational sociolinguistics.**

#### Rémi MUNOS

Google DeepMind

Title: **Introduction to distributional reinforcement learning.**

#### Konrad SCHINDLER

Professor – ETH Zürich

Title: **Computer vision and machine learning for environmental monitoring.**

#### Cordelia SCHMID

Research Director – INRIA

Title: **Action recognition.**

#### Ming YUAN

Professor – Columbia University

Title: **Low rank tensor methods in high dimensional data analysis.**

#### Melanie ZEILINGER

Assistant Professor – ETH Zürich

Eva-Mayr-Stihl Professor – University of Freiburg

Title: **Safe learning-based control.**

# Speakers / Guests (Thursday-Friday): In-depth Tutorial with Practical Session

#### Matthew B. BLASCHKO

Professor – KU Leuven

Title: **Hyper-parameter selection with Bayesian optimization.**

#### Diana BORSA

Google DeepMind

Title: **Shallow dive in deep reinforcement learning.**

#### Volkan CEVHER

Associate Professor – EPFL

Faculty Fellow – Rice University

Title: **Mathematics of data: From theory to computation.**

#### Armin EFTEKHARI

PostDoc – EPFL

(Volkan CEVHER‘s group)

Title: **Mathematics of data: From theory to computation.**

#### Olivier GRISEL

Software Engineer – INRIA

Title: **Introduction to deep learning with Keras.**

#### Hamed HASSANI

Assistant Professor – University of Pennsylvania

Title: **Theory and applications of submodular optimization: From discrete to continuous and back.**

#### Martin JAGGI

Assistant Professor – EPFL

Title: **Optimization for machine learning and deep learning.**

#### Olivier KOCH

Staff Machine Learning Lead – Criteo

Title: **Classical algorithms and matrix factorization.**

#### Mario LUCIC

Senior Research Scientist – Google Brain

Title: **Deep generative models.**

#### Marcin MICHALSKI

Software Engineer – Google Brain

Title: **Deep generative models.**

#### Evan OTT

PhD student – University of Texas at Austin

(Sinead WILLIAMSON‘s group)

Title: **Bayesian modeling and inference.**

#### Jonas PETERS

Associate Professor – University of Copenhagen

Title: **Causality.**

#### Bilal PIOT

Google DeepMind

Title: **Shallow dive in deep reinforcement learning.**

#### Amal RANNEN TRIKI

PhD student – KU Leuven & Yonsei University

(Matthew B. BLASCHKO‘s group)

Title: **Hyper-parameter selection with Bayesian optimization.**

#### Pierre H. RICHEMOND

PhD student – Imperial College London

(helping Bilal PIOT)

Title: **Shallow dive in deep reinforcement learning.**

#### Paul ROLLAND

PhD student – EPFL

(Volkan CEVHER‘s group)

Title: **Mathematics of data: From theory to computation.**

#### Thomas SANCHEZ

PhD student – EPFL

(Volkan CEVHER‘s group)

Title: **Mathematics of data: From theory to computation.**

#### Bharath K. SRIPERUMBUDUR

Assistant Professor – Pennsylvania State University

Title: **Learning with positive definite kernels: Theory, algorithms and applications**.

#### Dougal J. SUTHERLAND

PostDoc – University College London

(helping Bharath K. SRIPERUMBUDUR)

Title: **Learning with positive definite kernels: Theory, algorithms and applications**.

#### Flavien VASILE

Research Lead – Learning Representations team Criteo

Title: **Neural networks and causal recommendation.**

#### Thijs VOGELS

PhD student – EPFL

(Martin JAGGI‘s group)

Title: **Optimization for machine learning and deep learning.**

#### Sinead WILLIAMSON

Assistant Professor – University of Texas at Austin

Title: **Bayesian modeling and inference****.**

#### Steven R. WILSON

PostDoc – University of Michigan

(Rada MIHALCEA‘s group)

Title: **Fundamentals of text analysis for user generated content.**