Publications related to Laboratory for Information and Inference Systems

GANs for All: Supporting Fun and Intuitive Exploration of GAN Latent Spaces

Pierre Dillenbourg, Richard Lee Davis, Kevin Gonyop Kim, Wei Jiang

We have developed a new tool that makes it possible for people with zero programming experience to intentionally and meaningfully explore the latent space of a GAN. We combine a number of methods from the literature into a single system that includes multi ...

PMLR2022

Adjustable deterministic pseudonymization of speech

Mathew Magimai Doss, Subrahmanya Pavankumar Dubagunta

While public speech resources become increasingly available, there is a growing interest to preserve the privacy of the speakers, through methods that anonymize the speaker information from speech while preserving the spoken linguistic content. In this pap ...

ACADEMIC PRESS LTD- ELSEVIER SCIENCE LTD2022

Digital Doubles: The Major Agency of Minor Bits

Lucia-Nieves Garcia de Jalon Oyarzun

In a world that seeks to describe, codify and quantify everything, and particularly our viscerality and its interactions with our actual and digital environments, can we find interstitial spaces, currently unseen, unobserved and unlegislated, where we migh ...

2022

Semi-supervised Active Salient Object Detection

Tong Zhang

In this paper, we propose a novel semi-supervised active salient object detection (SOD) method that actively acquires a small subset of the most discriminative and representative samples for labeling. Two main contributions have been made to prevent the me ...

ELSEVIER SCI LTD2022

Safety in Numbers: Asymptotic Analysis of a Monitoring Problem

Emre Telatar, Reka Inovan

In this work, we introduce a setup where a monitoring entity attempts to distinguish a cheating player among a group of regular players where all players behave in order to maximize their reward. We assume that the cheating player has an "information advan ...

IEEE2022

Sparse-RS: A Versatile Framework for Query-Efficient Sparse Black-Box Adversarial Attacks

Nicolas Henri Bernard Flammarion, Maksym Andriushchenko, Francesco Croce

We propose a versatile framework based on random search, Sparse-RS, for score-based sparse targeted and untargeted attacks in the black-box setting. Sparse-RS does not rely on substitute models and achieves state-of-the-art success rate and query efficienc ...

ASSOC ADVANCEMENT ARTIFICIAL INTELLIGENCE2022

Adaptation in Stochastic Algorithms: From Nonsmooth Optimization to Min-Max Problems and Beyond

Ahmet Alacaoglu

Stochastic gradient descent (SGD) and randomized coordinate descent (RCD) are two of the workhorses for training modern automated decision systems. Intriguingly, convergence properties of these methods are not well-established as we move away from the spec ...

EPFL2021

Last iterate convergence of SGD for Least-Squares in the Interpolation regime

Nicolas Henri Bernard Flammarion, Aditya Vardhan Varre, Loucas Pillaud-Vivien

Motivated by the recent successes of neural networks that have the ability to fit the data perfectly \emph{and} generalize well, we study the noiseless model in the fundamental least-squares setup. We assume that an optimum predictor fits perfectly inputs ...

2021

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

Volkan Cevher, Maria-Luiza Vladarean

We consider the problem of finding a saddle point for the convex-concave objective

\min_x \max_y f(x) + \langle Ax, y\rangle - g^*(y)

, where

f

is a convex function with locally Lipschitz gradient and

g

is convex and possibly non-smooth. We propose an ...

2021

Convex optimization in sums of Banach spaces

Michaël Unser, Shayan Aziznejad

We characterize the solution of a broad class of convex optimization problems that address the reconstruction of a function from a finite number of linear measurements. The underlying hypothesis is that the solution is decomposable as a finite sum of compo ...

2021

Laboratory for Information and Inference Systems

Graph Chatbot

Chat with Graph Search

GANs for All: Supporting Fun and Intuitive Exploration of GAN Latent Spaces

Adjustable deterministic pseudonymization of speech

Digital Doubles: The Major Agency of Minor Bits

Semi-supervised Active Salient Object Detection

Safety in Numbers: Asymptotic Analysis of a Monitoring Problem

Sparse-RS: A Versatile Framework for Query-Efficient Sparse Black-Box Adversarial Attacks

Adaptation in Stochastic Algorithms: From Nonsmooth Optimization to Min-Max Problems and Beyond

Last iterate convergence of SGD for Least-Squares in the Interpolation regime

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

Convex optimization in sums of Banach spaces

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

GANs for All: Supporting Fun and Intuitive Exploration of GAN Latent Spaces

Adjustable deterministic pseudonymization of speech

Sparse-RS: A Versatile Framework for Query-Efficient Sparse Black-Box Adversarial Attacks

Adaptation in Stochastic Algorithms: From Nonsmooth Optimization to Min-Max Problems and Beyond

Convex optimization in sums of Banach spaces

Last iterate convergence of SGD for Least-Squares in the Interpolation regime

Digital Doubles: The Major Agency of Minor Bits

Safety in Numbers: Asymptotic Analysis of a Monitoring Problem

Semi-supervised Active Salient Object Detection