Research

Research is a major part in the Machine Learning field. With multiple publications each year, we are standing within the best.

2019

Mask Combination of Multi-layer Graphs for Global Structure Inference

E. Bayram; D. Thanou; E. Vural; P. Frossard 

2019-10-22. 

Extrapolating Paths with Graph Neural Networks

J-B. Cordonnier; A. Loukas 

2019-08-10. International Joint Conference on Artificial Intelligence, Macao, China, August 10-16, 2019.

Decentralized Stochastic Optimization and Gossip Algorithms with Compressed Communication

A. Koloskova; S. U. Stich; M. Jaggi 

2019-06-09. ICML 2019 – International Conference on Machine Learning, Long Beach, California, USA, 9-15 June 2019.

Memory Efficient Max Flow for Multi-Label Submodular MRFs

T. Ajanthan; R. Hartley; M. Salzmann 

IEEE Transactions On Pattern Analysis And Machine Intelligence (PAMI). 2019-04-01. Vol. 41, num. 4, p. 886-900. DOI : 10.1109/TPAMI.2018.2819675.

On the convergence of stochastic primal-dual hybrid gradient

A. Alacaoglu; O. Fercoq; V. Cevher 

2019

An adaptive primal-dual framework for nonsmooth convex minimization

Q. Tran-Dinh; A. Alacaoglu; O. Fercoq; V. Cevher 

Mathematical Programming Computation. 2019. Vol. [First Online]. DOI : 10.1007/s12532-019-00173-3.

Stochastic Frank-Wolfe for Composite Convex Minimization

F. Locatello; A. Yurtsever; O. Fercoq; V. Cevher 

2019. NeurIPS 2019 : Thirty-third Conference on Neural Information Processing Systems, Vancouver, Canada, December 8-14, 2019.

An Inexact Augmented Lagrangian Framework for Nonconvex Optimization with Nonlinear Constraints

M. F. Sahin; A. Eftekhari; A. Alacaoglu; F. R. Latorre Gomez; V. Cevher 

2019. NeurIPS 2019 : Thirty-third Conference on Neural Information Processing Systems, Vancouver, Canada, December 8-14, 2019.

Fast and Provable ADMM for Learning with Generative Priors

F. R. Latorre Gomez; A. Eftekhari; V. Cevher 

2019. NeurIPS 2019 : Thirty-third Conference on Neural Information Processing Systems, Vancouver, Canada, December 8-14, 2019.

UniXGrad: A Universal, Adaptive Algorithm with Optimal Guarantees for Constrained Optimization

A. Kavis; K. Y. Levy; F. Bach; V. Cevher 

2019. NeurIPS 2019 : Thirty-third Conference on Neural Information Processing Systems, Vancouver, Canada, December 8-14, 2019.

Error Feedback Fixes SignSGD and other Gradient Compression Schemes

S. P. R. Karimireddy; Q. Rebjock; S. U. Stich; M. Jaggi 

2019. 36th International Conference on Machine Learning (ICML) 2019, Long Beach, USA, June 9-15, 2019. p. 3252-3261.

Overcoming Multi-model Forgetting

Y. Benyahia; K. Yu; K. B. Smires; M. Jaggi; A. C. Davison et al. 

2019. ICML 2019 – 36th International Conference on Machine Learning, Long Beach, California, USA, June 09-15, 2019. p. 594-603.

Graph Reduction with Spectral and Cut Guarantees

A. Loukas 

Journal of Machine Learning Research. 2019. Vol. 20, num. 116, p. 1-42.

Walrasian Dynamics in Multi-unit Markets

S. Branzei; A. Filos-Ratsikas 

2019. 33rd AAAI Conference on Artificial Intelligence / 31st Innovative Applications of Artificial Intelligence Conference / 9th AAAI Symposium on Educational Advances in Artificial Intelligence, Honolulu, HI, Jan 27-Feb 01, 2019. p. 1812-1819.

Personalized Peer Truth Serum for Eliciting Multi-Attribute Personal Data

N. Goel; B. Faltings 

2019. 

Generating Artificial Data for Private Deep Learning

A. Triastcyn; B. Faltings 

2019. 

Deep Bayesian Trust : A Dominant and Fair Incentive Mechanism for Crowd

N. Goel; B. Faltings 

2019. 

Crowdsourcing with Fairness, Diversity and Budget Constraints

N. Goel; B. Faltings 

2019. 

Context-Tree Recommendation vs Matrix-Factorization: Algorithm Selection and Live Users Evaluation

S. Martin; B. Faltings; V. Schickel 

2019. 33rd AAAI Conference on Artificial Intelligence / 31st Innovative Applications of Artificial Intelligence Conference / 9th AAAI Symposium on Educational Advances in Artificial Intelligence, Honolulu, HI, Jan 27-Feb 01, 2019. p. 9534-9540.

Anytime Heuristic for Weighted Matching Through Altruism-Inspired Behavior

P. Danassis; A. Filos-Ratsikas; B. Faltings 

2019. 

Applications of Artificial Intelligence to Computational Chemistry

N. J. Browning / U. Röthlisberger (Dir.)  

Lausanne, EPFL, 2019. 

On Certifying Non-Uniform Bounds against Adversarial Attacks

C. Liu; R. Tomioka; V. Cevher 

2019. 36th International Conference on Machine Learning (ICML)’2019, Long Beach, USA, June 9-15, 2019.

[Re] Meta learning with differentiable closed-form solvers

A. Devos; S. Chatel; M. Grossglauser 

The ReScience journal C. 2019. 

Conditional Gradient Methods via Stochastic Path-Integrated Differential Estimator

A. Yurtsever; S. Sra; V. Cevher 

2019. 36th International Conference on Machine Learning (ICML 2019), Long Beach, USA, June 9-15, 2019.

Efficient learning of smooth probability functions from Bernoulli tests with guarantees.

P. T. Y. Rolland; A. Kavis; A. Immer; A. Singla; V. Cevher 

2019. 36th International Conference on Machine Learning (ICML 2019), Long Beach, USA, June 9-15, 2019.

A Conditional Gradient-Based Augmented Lagrangian Framework

A. Yurtsever; O. Fercoq; V. Cevher 

2019. 36th International Conference on Machine Learning (ICML 2019), Long Beach, USA, June 9-15, 2019.

Almost surely constrained convex optimization

O. Fercoq; A. Alacaoglu; I. Necoara; V. Cevher 

2019. 36th International Conference on Machine Learning (ICML 2019), Long Beach, USA, June 9-15, 2019.

Iterative Classroom Teaching

S. T. Yeo; K. Parameswaran; A. Singla; M. Arpit; T. L. C. Asselborn et al. 

2019. 33rd AAAI Conference on Artificial Intelligence / 31st Innovative Applications of Artificial Intelligence Conference / 9th AAAI Symposium on Educational Advances in Artificial Intelligence, Honolulu, Hawaii, USA, January 27 – February 1, 2019. p. 5684-5692.

2018

Training DNNs with Hybrid Block Floating Point

M. P. Drumond Lages De Oliveira; T. Lin; M. Jaggi; B. Falsafi 

2018-12-04. NeurIPS 2018 – Neural Information Processing Systems, Montréal Canada, December 2-8, 2018.

Accelerated Stochastic Matrix Inversion: General Theory and Speeding up BFGS Rules for Faster Second-Order Optimization

R. M. Gower; F. Hanzely; P. Richtárik; S. U. Stich 

2018-12-02. 32nd Annual Conference on Neural Information Processing Systems (NIPS), Montréal, Canada, December 2-8, 2018.

Sparsified SGD with Memory

S. U. Stich; J-B. Cordonnier; M. Jaggi 

2018-12-02. NeurIPS 2018 – 32nd Annual Conference on Neural Information Processing Systems, Montréal, Canada, December 2-8, 2018.

A Conditional Gradient Framework for Composite Convex Minimization with Applications to Semidefinite Programming

A. Yurtsever; O. Fercoq; F. Locatello; V. Cevher 

2018-07-11. the 35th International Conference on Machine Learning (ICML), Stockholm, Sweden, July 10-15, 2018.

Spectrally approximating large graphs with smaller graphs

A. Loukas; P. Vandergheynst 

2018-07-10. International Conference in Machine Learning (ICML), Stockholmsmässan, Sweden, July 10-15, 2018.

Online Adaptive Methods, Universality and Acceleration

K. Y. Levy; A. Yurtsever; V. Cevher 

2018-07-04. 32nd Conference on Neural Information Processing Systems conference (NIPS 2018), Montreal, Canada, December 3-8, 2018.

Optimal Distributed Learning with Multi-pass Stochastic Gradient Methods

J. Lin; V. Cevher 

2018-06-08. 35th International Conference on Machine Learning, Stockholm, Sweden, July 10 -15, 2018.

On Matching Pursuit and Coordinate Descent

F. Locatello; A. Raj; S. P. R. Karimireddy; G. Rätsch; B. Schölkopf et al. 

2018-05-01. ICML 2018 – 35th International Conference on Machine Learning.

Personalized and Private Peer-to-Peer Machine Learning

A. Bellet; R. Guerraoui; M. Taziki; M. Tommasi 

2018-04-09. AISTATS.

Optimal Rates of Sketched-regularized Algorithms for Least-Squares Regression over Hilbert Spaces

J. Lin; V. Cevher 

2018-03-11. 35th International Conference on Machine Learning (ICML), Stockholm, Sweden, July 10-15, 2018.

A Distributed Second-Order Algorithm You Can Trust

C. Mendler-Dünner; A. Lucchi; M. Gargiani; Y. A. Bian; T. Hofmann et al. 

2018. 35th International Conference on Machine Learning (ICML 2018), Stockholm, Sweden, 10-15 July 2018. p. 1358-1366.

Asynchronous Byzantine Machine Learning (the case of SGD)

G. Damaskinos; E. M. El Mhamdi; R. Guerraoui; R. Patra; M. Taziki 

2018. 35th International Conference on Machine Learning, Stockholm, SWEDEN, July 10-15, 2018. p. 1145-1154.

Non-Discriminatory Machine Learning through Convex Fairness Criteria

N. Goel; M. Yaghini; B. Faltings 

2018. 32nd AAAI Conference on Artificial Intelligence / 30th Innovative Applications of Artificial Intelligence Conference / 8th AAAI Symposium on Educational Advances in Artificial Intelligence, New Orleans, LA, February 02-07, 2018. p. 3029-3036.

Neural Tanget Kernel: Convergence and Generalization in Neural Networks

 

2018. NIPS’18 Proceedings of the 32nd International Conference on Neural Information Processing Systems, Montréal – Canada, December 3-8, 2018.

Online Adaptive Methods, Universality and Acceleration

K. Y. Levy; A. Yurtsever; V. Cevher 

2018-01-01. 32nd Conference on Neural Information Processing Systems (NIPS), Montreal, CANADA, Dec 02-08, 2018.

Mirrored Langevin Dynamics

Y-P. Hsieh; A. Kavis; P. Rolland; V. Cevher 

2018-01-01. 32nd Conference on Neural Information Processing Systems (NIPS), Montreal, CANADA, Dec 02-08, 2018.

Training DNNs with Hybrid Block Floating Point

M. Drumond; T. Lin; M. Jaggi; B. Falsafi 

2018-01-01. NeurIPS 2018 – 32nd Conference on Neural Information Processing Systems, Montreal, CANADA, Dec 02-08, 2018.

Adversarially Robust Optimization with Gaussian Processes

I. Bogunovic; J. Scarlett; S. Jegelka; V. Cevher 

2018. Conference on Neural Information Processing Systems (NIPS), Montreal, 2018.

Finding Mixed Nash Equilibria of Generative Adversarial Networks

Y-P. Hsieh; C. Liu; V. Cevher 

2018. IEEE International Conference on Machine Learning (ICML)’ 2019, Long Beach, USA, June 9-15, 2019.

The Hidden Vulnerability of Distributed Learning in Byzantium

E. M. El Mhamdi; R. Guerraoui; S. L. A. Rouault 

2018. International Conference on Machine Learning, Stockholm, Sweden, July 10-15, 2018.

Fast Approximate Spectral Clustering for Dynamic Networks

L. Martin; A. Loukas; P. Vandergheynst 

2018. International Conference in Machine Learning (ICML), Stockholmsmässan, Sweden, July 10-15, 2018.

Beyond Sharing Weights for Deep Domain Adaptation

A. Rozantsev; M. Salzmann; P. Fua 

IEEE Transactions on Pattern Analysis and Machine Intelligence. 2018. Vol. 41, num. 4, p. 801-814. DOI : 10.1109/TPAMI.2018.2814042.

Dimension-free Information Concentration via Exp-Concavity

Y-P. Hsieh; V. Cevher 

2018. Algorithmic Learning Theory (ALT) 2018, Lanzarote, Spain, April 7-9, 2018.

Robust Maximization of Non-Submodular Objectives

I. Bogunovic; J. Zhao; V. Cevher 

2018. International Conference on Artificial Intelligence and Statistics (AISTATS), Lanzarote, Canary Islands, April, 9-11, 2018.

High Dimensional Bayesian Optimization via Additive Models with Overlapping Groups

P. T. Y. Rolland; J. Scarlett; I. Bogunovic; V. Cevher 

2018. AISTATS, Lanzarote, Spain, April, 9-11, 2018.

Stochastic Three-Composite Convex Minimization with a Linear Operator

R. Zhao; V. Cevher 

2018. 21st International Conference on Artificial Intelligence and Statistics (AISTATS) 2018,, Lanzarotte, Spain, April 9-11, 2018.

Let’s be honest: An optimal no-regret framework for zero-sum games

E. Asadi Kangarshahi; Y-P. Hsieh; M. F. Sahin; V. Cevher 

2018. 35th International Conference on Machine Learning (ICML), Stockholm, Sweden, July 10-15, 2018.

2017

Fixed-Rank Approximation of a Positive-Semidefinite Matrix from Streaming Data

J. A. Tropp; A. Yurtsever; M. Udell; V. Cevher 

2017-12-04. 31st Annual Conference on Neural Information Processing Systems (NIPS), Long Beach, California, USA, December 4-9, 2017.

Deep Subspace Clustering Networks

P. Ji; T. Zhang; H. Li; M. Salzmann; I. Reid 

2017. Neural Information Processing Systems (NIPS).

Compression-aware Training of Deep Networks

J. Alvarez; M. Salzmann 

2017. Neural Information Processing Systems (NIPS).

Streaming Robust Submodular Maximization: A Partitioned Thresholding Approach

S. Mitrovic; I. Bogunovic; A. Norouzi Fard; J. Tarnawski; V. Cevher 

2017. Conference on Neural Information Processing Systems (NIPS), Long Beach,

Safe Adaptive Importance Sampling

S. U. Stich; A. Raj; M. Jaggi 

2017. Neural Information Processing Systems (NIPS), Long Beach, USA, December 4-9, 2017.

Smooth Primal-Dual Coordinate Descent Algorithms for Nonsmooth Convex Optimization

A. Alacaoglu; Q. Tran-Dinh; O. Fercoq; V. Cevher 

2017. 31st Conference on Neural Information Processing Systems (NIPS 2017), Long Beach, CA, USA, December 4-9, 2017.

Phase Transitions in the Pooled Data Problem

J. Scarlett; V. Cevher 

2017. Conference on Neural Information Processing Systems (NIPS), Long Beach, California, December 2017.

Combinatorial Penalties: Which structures are preserved by convex relaxations?

M. El Halabi; F. Bach; V. Cevher 

2017. 21st International Conference on Artificial Intelligence and Statistics (AISTATS), Lanzarotte, Spain , April 9-11, 2017.

On The Robustness of a Neural Network

E. M. El Mhamdi; R. Guerraoui; S. L. A. Rouault 

2017. 36th IEEE International Symposium on Reliable Distributed Systems, Hong Kong, September 26-29, 2017.

Approximate Steepest Coordinate Descent

S. U. Stich; A. Raj; M. Jaggi 

2017. ICML 2017 – International Conference on Machine Learning, Sydney, Australia, Aug 6-11, 2017.

Dynamic Safe Interruptibility for Decentralized Multi-Agent Reinforcement Learning

E. M. El Mhamdi; H. Hendrikx; R. Guerraoui; A. D. O. Maurer 

2017

Joint Dimensionality Reduction and Metric Learning: A Geometric Take

M. Harandi; M. Salzmann; R. Hartley 

2017. International Conference on Machine Learning (ICML).

ChoiceRank: Identifying Preferences from Node Traffic in Networks

L. Maystre; M. Grossglauser 

2017. International Conference on Machine Learning, Sydney, Australia, August 6-11, 2017.

Just Sort It! A Simple and Effective Approach to Active Preference Learning

L. Maystre; M. Grossglauser 

2017. International Conference on Machine Learning, Sydney, Australia, August 6-11, 2017.

Robust Submodular Maximization: A Non-Uniform Partitioning Approach

I. Bogunovic; S. Mitrovic; J. Scarlett; V. Cevher 

2017. The 34th International Conference on Machine Learning (ICML), Sydney, 2017.

Lower Bounds on Regret for Noisy Gaussian Process Bandit Optimization

J. Scarlett; I. Bogunovic; V. Cevher 

2017. Conference on Learning Theory (COLT)Conference on Learning Theory (COLT), AmsterdamAmsterdam, Netherlands, July 2017July, 7-10, 2017.

How close are the eigenvectors and eigenvalues of the sample and actual covariance matrices?

A. Loukas 

2017. International Conference on Machine Learning (ICML), Sydney, August 8-11, 2017.

Faster Coordinate Descent via Adaptive Importance Sampling

D. Perekrestenko; V. Cevher; M. Jaggi 

2017. 20th International Conference on Artificial Intelligence and Statistics (AISTATS) 2017, Fort Lauderdale, Florida, USA, April 20-22, 2017.

Sketchy Decisions: Convex Low-Rank Matrix Optimization with Optimal Storage

A. Yurtsever; M. Udell; J. A. Tropp; V. Cevher 

2017. 20th International Conference on Artificial Intelligence and Statistics (AISTATS2017), Fort Lauderdale, Florida, USA, April 20-22, 2017.

Lower Bounds on Active Learning for Graphical Model Selection

J. Scarlett; V. Cevher 

2017. The 20th International Conference on Artificial Intelligence and Statistics (AISTATS 2017), Fort Lauderdale, Florida, USA, April 20-22, 2017.

2016

Primal-Dual Rates and Certificates

C. Dünner; S. Forte; M. Takác; M. Jaggi 

2016. ICML 2016 – International Conference on Machine Learning, USA, NY, New York City, June 19-24, 2016. p. 783-792.

Distribution-Matching Embedding for Visual Domain Adaptation

M. Baktashmotlagh; M. Harandi; M. Salzmann 

Journal Of Machine Learning Research. 2016. Vol. 17, p. 108.

An Efficient Streaming Algorithm for the Submodular Cover Problem

A. Norouzi Fard; A. Bazzi; M. El Halabi; I. Bogunovic; Y-P. Hsieh et al. 

2016. The Thirtieth Annual Conference on Neural Information Processing Systems (NIPS).

Learning the Number of Neurons in Deep Networks

J. M. Alvarez; M. Salzmann 

2016. Conference on Neural Information Processing Systems (NIPS), Barcelona, Spain,

Stochastic Three-Composite Convex Minimization

A. Yurtsever; C. B. Vu; V. Cevher 

2016. 30th Conference on Neural Information Processing Systems (NIPS2016), Barcelona, Spain, December 5-10, 2016.

Truncated Variance Reduction: A Unified Approach to Bayesian Optimization and Level-Set Estimation

I. Bogunovic; J. Scarlett; A. Krause; V. Cevher 

2016. Conference on Neural Information Processing Systems (NIPS), Barcelona, December 5-10, 2016.

Convex block-sparse linear regression with expanders – provably

A. Kyrillidis; B. Bah; R. Hasheminezhad; Q. Tran Dinh; L. Baldassarre et al. 

2016. The 19th International Conference on Artificial Intelligence and Statistics (AISTATS 2016), Cadiz, Spain, May 7-11, 2016.

Time-Varying Gaussian Process Bandit Optimization

I. Bogunovic; J. Scarlett; V. Cevher 

2016. International Conference on Artificial Intelligence and Statistics (AISTATS), Cadiz, Spain, May 9 – 11, 2016.

Limits on Sparse Support Recovery via Linear Sketching with Random Expander Matrices

J. Scarlett; V. Cevher 

2016. International Conference on Artificial Intelligence and Statistics (AISTATS), Cadiz, Spain, May 9-11, 2016.

2015

Personalizing Product Rankings Using Collaborative Filtering on Opinion-Derived Topic Profiles

C. C. Musat; B. Faltings 

24th IJCAI. 2015.  p. 830-836.

On the Global Linear Convergence of Frank-Wolfe Optimization Variants

S. Lacoste-Julien; M. Jaggi 

2015. Neural Information Processing Systems (NIPS) 2015, Montreal, Quebec, Canada, December 7-12, 2015. p. 496-504.

Adding vs. Averaging in Distributed Primal-Dual Optimization

C. Ma; V. Smith; M. Jaggi; M. I. Jordan; P. Richtárik et al. 

2015. ICML 2015 – International Conference on Machine Learning, Lille, France, 6-11 July 2015. p. 1973-1982.

Incentives for Subjective Evaluations with Private Beliefs

G. Radanovic; B. Faltings 

2015. The 29th AAAI Conference on Artificial Intelligence (AAAI’15). p. 1014-1020.

Fast and Accurate Inference of Plackett-Luce Models

L. Maystre; M. Grossglauser 

2015. Neural Information Processing Systems (NIPS), Montreal, Quebec, Canada, December 7-12, 2015.

Preconditioned Spectral Descent for Deep Learning

D. Carlson; E. Collins; Y-P. Hsieh; L. Carin; V. Cevher 

2015. 29-th Neural Information Processing Systems (NIPS), 2015.

A Universal Primal-Dual Convex Optimization Framework

A. Yurtsever; Q. Tran Dinh; V. Cevher 

2015. 29th Annual Conference on Neural Information Processing Systems (NIPS2015), Montreal, Canada, December 7-12, 2015.

Stochastic Spectral Descent for Restricted Boltzmann Machines.

D. Carlson; V. Cevher; L. Carin 

2015. The 18th International Conference on Artificial Intelligence and Statistics, San Diego, USA, May 9-12, 2015.

Sparsistency of $\ell_1$-Regularized $M$-Estimators

Y-H. Li; J. Scarlett; P. Ravikumar; V. Cevher 

2015. The 18th International Conference on Artificial Intelligence and Statistics, San Diego, California, USA, May 9-12, 2015.

A totally unimodular view of structured sparsity

M. El Halabi; V. Cevher 

2015. The 18th International Conference on Artificial Intelligence and Statistics, San Diego, California, USA, May 9 – 12, 2015.

2014

Acquiring Commonsense Knowledge for Sentiment Analysis through Human Computation\_1

M. Boia; C. C. Musat; B. Faltings 

2014.  p. 901-907.

A Region-Based Model for Estimating Urban Air Pollution

A. Jutzeler; J. J. Li; B. Faltings 

2014.  p. 424-430.

Communication-Efficient Distributed Dual Coordinate Ascent.

M. Jaggi; V. Smith; M. Takác; J. Terhorst; S. Krishnan et al. 

2014. Neural Information Processing Systems (NIPS) 2014, Montreal, Quebec, Canada, December 8-13 2014. p. 3068-3076.

Incentives for Truthful Information Elicitation of Continuous Signals

G. Radanovic; B. Faltings 

2014. The 28th AAAI Conference on Artificial Intelligence (AAAI’14). p. 770-776.

Time–Data Tradeoffs by Aggressive Smoothing

J. J. Bruer; J. A. Tropp; V. Cevher; S. R. Becker 

2014. Conference of Neural Information Processing Systems (NIPS) Foundation 2014, Montreal, Quebec, Canada, December 8-11, 2014.

Constrained convex minimization via model-based excessive gap

Q. Tran Dinh; V. Cevher 

2014. Advances in Neural Information Processing Systems (NIPS) 2014, Montreal, Quebec, Canada, December 8-11, 2014.