Research

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

2022

Karl Jaspers and artificial neural nets: on the relation of explaining and understanding artificial intelligence in medicine

G. Starke; C. Poppe 

Ethics And Information Technology. 2022-09-01. Vol. 24, num. 3, p. 26. DOI : 10.1007/s10676-022-09650-1.

BIGPrior: Towards Decoupling Learned Prior Hallucination and Data Fidelity in Image Restoration

M. El Helou; S. Süsstrunk 

IEEE Transactions on Image Processing. 2022-01-08. Vol. 31, p. 1-13. DOI : 10.1109/TIP.2022.3143006.

Score Matching Enables Causal Discovery of Nonlinear Additive Noise Models

P. T. Y. Rolland; V. Cevher; M. Kleindessner; C. Russel; B. Schölkopf et al. 

2022. 39th International Conference on Machine Learning (ICML 2022), Baltimore, Maryland, USA, July 17-23, 2022.

High Probability Bounds for a Class of Nonconvex Algorithms with AdaGrad Stepsize

A. Kavis; K. Levy; V. Cevher 

2022. 10th International Conference on Learning Representations (ICLR), Virtual, April 25-29, 2022.

Controlling the Complexity and Lipschitz Constant improves Polynomial Nets

Z. Zhenyu; F. Latorre; G. Chrysos; V. Cevher 

2022. 10th International Conference on Learning Representations (ICLR), Virtual, April 25-29, 2022.

The spectral bias of polynomial neural networks

M. Choraria; L. T. Dadi; G. Chrysos; J. Mairal; V. Cevher 

2022. 10th International Conference on Learning Representations (ICLR), Virtual, April 25-29, 2022.

Escaping limit cycles: Global convergence for constrained nonconvex-nonconcave minimax problems

T. M. Pethick; P. Latafat; P. Patrinos; O. Fercoq; V. Cevher 

2022. 10th International Conference on Learning Representations (ICLR 2022), Virtual, April 25-29, 2022.

2021

Local plasticity rules can learn deep representations using self-supervised contrastive predictions

B. A. Illing; J. Ventura; G. Bellec; W. Gerstner 

35th Conference on Neural Information Processing Systems (NeurIPS 2021), Online, December 6-14, 2021.

Collaborative Learning in the Jungle (Decentralized, Byzantine, Heterogeneous, Asynchronous and Nonconvex Learning)

E. M. El Mhamdi; S. Farhadkhani; R. Guerraoui; A. H. A. Guirguis; L. N. Hoang et al. 

2021-12-06. 35th Conference on Neural Information Processing Systems (NeurIPS 2021), Virtual, December 6-14, 2021.

What can linearized neural networks actually say about generalization?

G. Ortiz Jimenez; S. M. Moosavi Dezfooli; P. Frossard 

2021-12-06. Thirty-fifth Conference on Neural Information Processing Systems (NeurIPS 2021), Virtual, December 6-14, 2021.

Machine Learning Uncovers Aerosol Size Information From Chemistry and Meteorology to Quantify Potential Cloud-Forming Particles

A. A. Nair; F. Yu; P. Campuzano-Jost; P. J. DeMott; E. J. T. Levin et al. 

Geophysical Research Letters. 2021-11-16. Vol. 48, num. 21, p. e2021GL094133. DOI : 10.1029/2021GL094133.

GARFIELD: System Support for Byzantine Machine Learning (Regular Paper)

R. Guerraoui; A. Guirguis; J. Plassmann; A. Ragot; S. Rouault 

2021-06-21. 2021 51st Annual IEEE/IFIP International Conference on Dependable Systems and Networks (DSN), Taipei, Taiwan, June 21-24, 2021. p. 39-51. DOI : 10.1109/DSN48987.2021.00021.

Geometry of the Loss Landscape in Overparameterized Neural Networks: Symmetries and Invariances

B. Şimşek; F. Ged; A. Jacot; F. Spadaro; C. Hongler et al. 

2021. 38 th International Conference on Machine Learning (ICML 2021), Virtual, July 18-24, 2021. p. 9722-9732.

Fitting summary statistics of neural data with a differentiable spiking network simulator

G. Bellec; S. Wang; A. Modirshanechi; J. M. Brea; W. Gerstner 

35th Conference on Neural Information Processing Systems (NeurIPS 2021), Online, December 6-14, 2021.

Mixed Nash Equilibria in the Adversarial Examples Game

L. Meunier; M. Scetbon; R. Pinot; J. Atif; Y. Chevaleyre 

2021. 38th International Conference on Machine Learning (ICML 2021), Online, July 18-24, 2021. p. 7677-7687 .

A Plug-and-Play Deep Image Prior

Z. Sun; F. Latorre; T. Sanchez; V. Cevher 

2021. International Conference on Acoustics, Speech, and Signal Processing (ICASSP 2021), Toronto, Canada, June 6-11, 2021. DOI : 10.1109/ICASSP39728.2021.9414879.

Sifting through the Noise: Universal First-Order Methods for Stochastic Variational Inequalities

K. Antonakopoulos; T. M. Pethick; A. Kavis; P. Mertikopoulos; V. Cevher 

2021. NeurIPS 2021 : Thirty-fifth Conference on Neural Information Processing Systems, Sydney, Australia [Virtual only], December 6-14, 2021.

Convergence of adaptive algorithms for constrained weakly convex optimization

A. Alacaoglu; Y. Malitskyi; V. Cevher 

2021. 35th Conference on Neural Information Processing Systems (NeurIPS 2021), Sydney, Australia, December 6-14, 2021.

STORM+: Fully Adaptive SGD with Momentum for Nonconvex Optimization

K. Levy; A. Kavis; V. Cevher 

2021. 35th Conference on Neural Information Processing Systems (NeurIPS 2021), Sydney, Australia, December 6-14, 2021.

A first-order primal-dual method with adaptivity to local smoothness

M-L. Vladarean; Y. Malitsky; V. Cevher 

2021. 35th Conference on Neural Information Processing Systems (NeurIPS 2021), Sydney, Australia, December 6-14, 2021.

Robust Inverse Reinforcement Learning under Transition Dynamics Mismatch

L. Viano; Y-T. Huang; K. Parameswaran; A. Weller; V. Cevher 

2021. 35th Conference on Neural Information Processing Systems (NeurIPS 2021), Sydney, Australia, December 6-14, 2021.

The Effect of the Intrinsic Dimension on the Generalization of Quadratic Classifiers

F. Latorre; L. T. Dadi; P. T. Y. Rolland; V. Cevher 

2021. 35th Conference on Neural Information Processing Systems (NeurIPS 2021), Sydney, Australia, December 6-14, 2021.

Subquadratic Overparameterization for Shallow Neural Networks

C. Song; A. Ramezani-Kebrya; T. Pethick; A. Eftekhari; V. Cevher 

2021. 35th Conference on Neural Information Processing Systems (NeurIPS 2021), Sydney, Australia, December 6-14, 2021.

Regret Minimization in Stochastic Non-Convex Learning via a Proximal-Gradient Approach

N. Hallak; P. Mertikopoulos; V. Cevher 

2021-01-01. International Conference on Machine Learning (ICML), ELECTR NETWORK, Jul 18-24, 2021.

Critical Parameters for Scalable Distributed Learning with Large Batches and Asynchronous Updates

S. U. Stich; A. Mohtashami; M. Jaggi 

2021. 24th International Conference on Artificial Intelligence and Statistics (AISTATS), Virtual, April 13-15, 2021.

Lifelong Machine Learning with Data Efficiency and Knowledge Retention

F. Mi / B. Faltings (Dir.)  

Lausanne, EPFL, 2021. 

The Limits of Min-Max Optimization Algorithms: Convergence to Spurious Non-Critical Sets

Y-P. Hsieh; P. Mertikopoulos; V. Cevher 

2021. 38th International Conference on Machine Learning (ICML 2021), Online, July 18-24, 2021. p. 4337-4348.

2020

FeGAN: Scaling Distributed GANs

R. Guerraoui; A. Guirguis; A-M. Kermarrec; E. L. Merrer 

2020-12-10. 21st International Middleware Conference, Delft, Netherlands, December 7-11, 2020. p. 193-206. DOI : 10.1145/3423211.3425688.

Robust Reinforcement Learning via Adversarial training with Langevin Dynamics

K. Parameswaran; Y-T. Huang; Y-P. Hsieh; P. T. Y. Rolland; C. Shi et al. 

2020-11-05

DeepSVG: A Hierarchical Generative Network for Vector Graphics Animation

A. Carlier; M. Danelljan; A. Alahi; R. Timofte 

2020-09-29. NeurIPS 2020 34th Conference on Neural Information Processing Systems, Vancouver, Canada, December 6-12, 2020.

Genuinely Distributed Byzantine Machine Learning

E. M. El Mhamdi; R. Guerraoui; A. H. A. Guirguis; L. N. Hoang; S. L. A. Rouault 

2020-08-03. The ACM Symposium on Principles of Distributed Computing (PODC), Salerno, Italy, August 3–7, 2020. DOI : 10.1145/3382734.3405695.

CUMULATOR — a tool to quantify and report the carbon footprint of machine learning computations and communication in academia and healthcare

T. Trébaol 

2020-06-19.

Lipschitz constant estimation for Neural Networks via sparse polynomial optimization

F. Latorre; P. T. Y. Rolland; V. Cevher 

2020-04-26. 8th International Conference on Learning Representations, Addis Ababa, ETHIOPIA, April 26-30, 2020.

Collaborative Sampling in Generative Adversarial Networks

Y. Liu; P. A. Kothari; A. Alahi 

2020-02-11. Thirty-Fourth AAAI Conference on Artificial Intelligence (AAAI-20), New York, New York, USA, February 7-12, 2020. p. 4948-4956. DOI : 10.1609/aaai.v34i04.5933.

On the Almost Sure Convergence of Stochastic Gradient Descent in Non-Convex Problems

P. Mertikopoulos; N. Hallak; A. Kavis; V. Cevher 

2020. 34th Conference on Neural Information Processing Systems (NeurIPS 2020), Virtual, December 6-12, 2020.

A Linearly Convergent Algorithm for Decentralized Optimization: Sending Less Bits for Free!

D. Kovalev; A. Koloskova; M. Jaggi; P. Richtarik; U. S. Sitch 

2020. 24th International Conference on Artificial Intelligence and Statistics (AISTATS), Virtual, April 13-15, 2021.

Practical Low-Rank Communication Compression in Decentralized Deep Learning

T. Vogels; S. P. R. Karimireddy; M. Jaggi 

2020. NeurIPS 2020 – Advances in Neural Information Processing Systems, Virtual, December 6-12, 2020.

Ensemble Distillation for Robust Model Fusion in Federated Learning

T. Lin; L. Kong; S. U. Stich; M. Jaggi 

2020. NeurIPS 2020 – Advances in Neural Information Processing Systems, Virtual, April 13-15, 2021.

Model Fusion via Optimal Transport

S. P. Singh; M. Jaggi 

2020. NeurIPS 2020 – Advances in Neural Information Processing Systems, Virtual, April 13-15, 2021.

Extrapolation for Large-batch Training in Deep Learning

T. Lin; L. Kong; S. U. Stich; M. Jaggi 

2020. ICML 2020 37th International Conference on Machine Learning, Virtual, July 13-18, 2020.

A Unified Theory of Decentralized SGD with Changing Topology and Local Updates

A. Koloskova; N. Loizou; S. Boreiri; M. Jaggi; S. U. Stich 

2020. 37th International Conference on Machine Learning (ICML 2020), Virtual, July 13-18, 2020.

Detection of Similar Languages and Dialects Using Deep Supervised Autoencoders

S. Parida; E. Villatoro-Tello; S. Kumar; M. Fabien; P. Motlicek 

2020. 17th International Conference on Natural Language Processing, 1-7 December 2020. p. 362–367.

BertAA: BERT fine-tuning for Authorship Attribution

M. Fabien; E. Villatoro-Tello; P. Motlicek; S. Parida 

2020. 17th International Conference on Natural Language Processing, 1-7 December 2020.

Vulnerability Analysis of Face Morphing Attacks from Landmarks and Generative Adversarial Networks

E. Sarkar; P. Korshunov; L. Colbois; S. Marcel 

2020

//www.idiap.ch/en/dataset/frgc-morphs.

//www.idiap.ch/en/dataset/frgc-morphs.

UCLID-Net: Single View Reconstruction in Object Space

B. Guillard; E. Remelli; P. Fua 

2020. 34th Conference on Neural Information Processing Systems, Virtual, December 6-12, 2020.

Neural Anisotropy Directions

G. Ortiz Jimenez; A. Modas; S. M. Moosavi Dezfooli; P. Frossard 

2020. NeurIPS 2020 34th Conference on Neural Information Processing Systems, Vancouver, Canada, December 6-12, 2020.

Hold me tight! Influence of discriminative features on deep network boundaries

G. Ortiz Jimenez; A. Modas; S. M. Moosavi Dezfooli; P. Frossard 

2020. Thirty-fourth Conference on Neural Information Processing Systems (NeurIPS 2020), [Virtual only], December 6-12, 2020.

Conditional gradient methods for stochastically constrained convex minimization

M-L. Vladarean; A. Alacaoglu; Y-P. Hsieh; V. Cevher 

2020. 37th International Conference on Machine Learning (ICML), virtual, July 12-18, 2020.

Efficient Proximal Mapping of the 1-path-norm of Shallow Networks

F. Latorre; P. T. Y. Rolland; S. N. Hallak; V. Cevher 

2020. 37th International Conference on Machine Learning (ICML), Virtual, July 13-18, 2020.

A new regret analysis for Adam-type algorithms

A. Alacaoglu; Y. Malitsky; P. Mertikopoulos; V. Cevher 

2020. 37th International Conference on Machine Learning (ICLM 2020), Virtual, July 13-18, 2020.

Adaptive Gradient Descent without Descent

Y. Malitsky; K. Mishchenko 

2020. 37th International Conference on Machine Learning (ICML 2020), Virtual, July 12-18, 2020.

Double-Loop Unadjusted Langevin Algorithm

P. Rolland; A. Eftekhari; A. Kavis; V. Cevher 

2020. 37th International Conference on Machine Learning (ICLM 2020), Virtual, July 12-18, 2020.

What graph neural networks cannot learn: depth vs width

A. Loukas 

2020. International Conference on Learning Representations, Addis Ababa, Ethiopia, April 26-30, 2020.

On the Relationship between Self-Attention and Convolutional Layers

J-B. Cordonnier; A. Loukas; M. Jaggi 

2020. Eighth International Conference on Learning Representations – ICLR 2020, Addis Ababa, Ethiopia, April 26-30, 2020.

Domain-Adaptive Multibranch Networks

R. Bermúdez Chacón; M. Salzmann; P. Fua 

2020. International Conference on Learning Representations (ICLR), Addis Ababa, Ethiopia, April 26-30, 2020.

An adaptive primal-dual framework for nonsmooth convex minimization

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

Mathematical Programming Computation. 2020. Vol. 12, p. 451–491. DOI : 10.1007/s12532-019-00173-3.

Personalized Peer Truth Serum for Eliciting Multi-Attribute Personal Data

N. Goel; B. Faltings 

2020-01-01. 35th Uncertainty in Artificial Intelligence (UAI) Conference, Tel Aviv, ISRAEL, Jul 22-25, 2019. p. 18-27.

2019

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. p. 2187–2194.

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.

AGGREGATHOR: Byzantine Machine Learning via Robust Gradient Aggregation

G. Damaskinos; E. M. El Mhamdi; R. Guerraoui; A. H. A. Guirguis; S. L. A. Rouault 

2019-04-01. The Conference on Systems and Machine Learning (SysML), 2019, Stanford, CA, USA, March 31 – April 2, 2019 .

Decentralized deep learning with arbitrary communication compression

A. Koloskova; T. Lin; S. U. Stich; M. Jaggi 

2019. ICLR 2020 8th International Conference on Learning Representations, Addis Ababa, Ethiopia, April 26-30, 2020.

Don’t Use Large Mini-Batches, Use Local SGD

T. Lin; S. U. Stich; K. K. Patel; M. Jaggi 

2019. ICLR 2020 8th International Conference on Learning Representations, Addis Ababa, Ethiopia, April 26-30, 2020.

On the convergence of stochastic primal-dual hybrid gradient

A. Alacaoglu; O. Fercoq; V. Cevher 

2019

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. 33rd Conference on Neural Information Processing Systems (NeurIPS), 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. 33rd Conference on Neural Information Processing Systems (NeurIPS), 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. DOI : 10.1609/aaai.v33i01.33011812.

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. 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. 1996-2003. DOI : 10.1609/aaai.v33i01.33011996.

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. DOI : 10.1609/aaai.v33i01.33019534.

Anytime Heuristic for Weighted Matching Through Altruism-Inspired Behavior

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

2019.  p. 215–222.

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. DOI : 10.1609/aaai.v33i01.33015684.

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. p. 6500-6509.

Decoupling Backpropagation using Constrained Optimization Methods

A. Gotmare; V. Thomas; J. M. Brea; M. Jaggi 

2018-06-18. ICML 2018 35th International Conference on Machine Learning, Stockholm, SWEDEN, July 10-15, 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. DOI : 10.1609/aaai.v32i1.11662.

Neural Tanget Kernel: Convergence and Generalization in Neural Networks

A. U. Jacot-Guillarmod; F. R. Gabriel; C. Hongler 

2018. 32nd International Conference on Neural Information Processing Systems, Montréal – Canada, December 3-8, 2018. p. 8580-8589.

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.