Walid Krichene
I am a member of the Laser group at Google Research, where I work on machine learning and recommendation. I also work on developing optimization methods using continuoustime and stochastic dynamics.
I did my Ph.D. in Electrical Engineering and Computer Sciences at UC Berkeley, where I was advised by Alex Bayen and Peter Bartlett. My thesis was on Continuous and discrete time dynamics for online learning and convex optimization.
News
 I will be one of the speakers at the Bay Area Optimization meeting (BayOpt 2018) on May 18 2018.
 I will give a talk on continuoustime optimization methods at the Machine Learning and Trends in Optimization seminar at the University of Washington, on February 20, 2018. slides
 Our paper on Acceleration and Averaging in Stochastic Descent Dynamics is selected for a spotlight presentation at NIPS. arxiv spotlight video
Publications
Thesis

W. Krichene. Continuous and Discrete Time Dynamics for Online Learning and Convex Optimization.
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2018

W. Krichene, M. C. Bourguiba, K. Lam, and A. Bayen. On Learning How Players Learn: Estimation of Learning Dynamics in the Routing Game.
ACM Transactions on CyberPhysical Systems  Special Issue.
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2017

W. Krichene and P. Bartlett. Acceleration and Averaging in Stochastic Descent Dynamics.
31st Annual Conference on Neural Information Processing Systems (NIPS).
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W. Krichene, J. D. Reilly, S. Amin, and A. Bayen. Stackelberg Routing on Parallel Transportation Networks. Book Chapter. In: Basar T., Zaccour G. (eds) Handbook of Dynamic Game Theory. Springer.
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2016

W. Krichene, A. Bayen and P. Bartlett. Adaptive Averaging in Accelerated Descent Dynamics.
30th Annual Conference on Neural Information Processing Systems (NIPS).
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M. Balandat, W. Krichene, A. Bayen and C. Tomlin. Minimizing regret on reflexive Banach spaces and Nash equilibria in continuous zerosum games.
30th Annual Conference on Neural Information Processing Systems (NIPS).
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W. Krichene, M. Suarez Castillo, and A. Bayen. On Social Optimal Routing Under Selfish Learning. Transactions on Contol of Network Systems (TCNS).
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2015

W. Krichene, A. Bayen, P. Bartlett. Accelerated Mirror Descent in Continuous and Discrete Time.
29th Annual Conference on Neural Information Processing Systems (NIPS).
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W. Krichene, S. Krichene, and A. Bayen. Efficient Bregman Projections onto the Simplex. 54th IEEE Conference on Decision and Control (CDC).
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W. Krichene, B. Drighes, and A. Bayen. Online Learning of Nash Equilibria in Congestion Games. SIAM Journal on Control and Optimization, 53(2), 1056–1081.
bibtex abstract arxiv

S. Krichene, W. Krichene, R. Dong, and A. Bayen. Convergence of Heterogeneous Distributed Learning in Stochastic Routing Games. 53rd Annual Allerton Conference on Communication, Control, and Computing.
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R. Dong, W. Krichene, A. Bayen, and S. Sastry. Differential Privacy of Populations in the Routing Game. 54th IEEE Conference on Decision and Control (CDC).
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W. Krichene, M. Balandat, C. Tomlin, and A. Bayen. The Hedge Algorithm on a Continuum. International Conference on Machine Learning (ICML).
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Z. Abrams Bayen, S. Chen, J. W. Frank, A. Gorajek, W. Krichene, and Itamar Rossen. Systems and Methods for Estimating User Attention (Patent No US20150142954 A1).
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2014

W. Krichene, B. Drighes, and A. Bayen. On the Convergence of NoRegret Learning in Selfish Routing. 31st International Conference on Machine Learning (ICML).
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B. Drighes, W. Krichene, and A. Bayen. Stability of Nash Equilibria in the Congestion Game under Replicator Dynamics. 53rd IEEE Conference on Decision and Control (CDC).
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W. Krichene, J. Reilly, S. Amin, A. Bayen. Stackelberg Routing on Parallel Networks with Horizontal Queues. IEEE Transactions on Automatic Control (TAC).
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J. Reilly, S. Samaranayake, M. Delle Monache, W. Krichene, P. Goatin, and A. Bayen. Adjointbased optimization on a network of discretized scalar conservation law PDEs with applications to coordinated ramp metering. Journal of Optimization Theory and Applications (JOTA).
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M. Delle Monache, J. Reilly, S. Samaranayake, W. Krichene, P. Goatin, and A. Bayen. A PDEODE Model for a Junction with Ramp Buffer. SIAM Journal on Applied Mathematics.
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Selected talks
Bay Area Optimization Meeting (BayOpt 2018).
Stanford University. May 19, 2018.
Continuoustime dynamics for optimization.
University of Washington. Feb. 20, 2018.
slides
Acceleration and Averaging in Stochastic Descent Dynamics.
Mountain View, CA. Nov. 2017.
Acceleration and Averaging in Stochastic Descent Dynamics.
Long Beach, CA. Dec. 5, 2017.
poster session video
Adaptive Averaging in Accelerated Descent Dynamics.
Barecelona, Spain. Dec. 2016.
poster
Continuous and Discrete Dynamics for Online Learning and Convex Optimization.
Berkeley, CA. August 18, 2016.
slides
Online Learning and Optimization: From Continuous to Discrete.
Boston, MA. April 5, 2016.
slides
Online Learning and Optimization: From Continuous to Discrete Time.
New York, NY. Feb. 18, 2016.
Accelerated Mirror Descent in Continuous and Discrete Time.
Montreal, Canada. Dec. 2015.
poster
Distributed Learning in Routing Games: Convergence, Estimation of Player Dyanmics, and Control.
Los Angeles, CA. Nov. 18, 2015.
slides
video
Efficient Bregman Projections onto the Simplex.
Osaka, Japan. Dec. 16, 2015.
slides
Distributed learning dynamics: Convergence in routing games and beyond.
KAUST. Oct. 7, 2015.
slides
Archive
Teaching
Berkeley MFE230P Fall 2014 
Optimization Methods for Finance. Recipient of the Berkeley Outstanding Graduate Student Instructor Award (2015). 

Berkeley EE128 Fall 2013 
Feedback Control Systems. Recipient of the EECS Outstanding Graduate Instructor Award (2014). 
student project videos 
Mentoring (visiting research students)
Chedly Bourguiba  Behavioral modeling using online learning.  From Ecole Polytechnique. Spring 2016 
Syrine Krichene  Stochastic optimization with applications to distributed routing.  From ENSIMAG. Summer 2014 
Milena Suarez Castillo  Online learning and control of Hedge dynamics.  From Ecole Polytechnique. Summer 2014 
Benjamin Drighès  Repeated routing, online learning, and noregret algorithms. Benjamin received the Grand Prix d'option of Ecole Polytechnique.  From Ecole Polytechnique. Summer 2013 
Yasser El Jebbari  Stackelberg thresholds for routing games.  From Ecole Polytechnique. Spring 2012 
Notes and old projects
Reading group (2015)  Convex Analysis, Rockafellar  notes 
Reading group (2013)  Prediction, Learning and Games, N. CesaBianchi and G. Lugosi  chap 2 chap 4 chap 5 chap 7 chap 7 bis 
Berkeley EECS 227C (2014)  Large Scale Optimization  HW01 HW02 HW03 
Berkeley STAT 205A (2013)  Probability Theory  HW01 HW02 HW03 HW04 HW05 
Berkeley CS 270 (2013)  Randomized Algorithms and Data Structures  HW01 HW02 HW03 HW04 
Berkeley MATH 202B (2013)  Topology and Measure Theory  HW01 HW02 HW03 HW04 HW05 HW06 HW08 HW09 HW10 HW11 
Berkeley MATH 202A (2012)  Introduction to Topology and Analysis  HW01 HW02 HW03 HW04 HW05 HW06 HW07 HW08 HW09 HW10 HW11 HW12 HW13 
Berkeley EE 227A (2012)  Convex Optimization  PCA and SVD Robust PCA 
Puzzles  Coupon collector problem Array balancing Goro sort (Google Code Jam) 
coupons arrays Goro 
Travel time estimation (2010)  Internship report and presentation (CCIT)  report slides 
Tictactoe on a cube (2008)  Project report (Ecole des Mines de Paris), in French.  report game 
Theorema Egregium (2007)  Project report (Lycée Louis Le Grand), in French. 
report 