Publications related to Ensembles for sequence learning

SKA Science Data Challenge 2: analysis and results

Yi Zhang, Xin Chen, Jean-Paul Richard Kneib, Frédéric Courbin, Jean-Luc Starck, Aymeric Alexandre Galan, Austin Chandler Peel, Emma Elizabeth Tolley, Lei Zhang, Hua Zhang, Xiuwei Zhang, Libo Yu, Claudio Gheller, Mark Thomas Sargent, Yi Wang

The Square Kilometre Array Observatory (SKAO) will explore the radio sky to new depths in order to conduct transformational science. SKAO data products made available to astronomers will be correspondingly large and complex, requiring the application of ad ...

OXFORD UNIV PRESS2023

Alternation makes the adversary weaker in two-player games

Volkan Cevher, Efstratios Panteleimon Skoulakis, Luca Viano, Ali Kavis

Motivated by alternating game-play in two-player games, we study an altenating variant of the Online Linear Optimization (OLO). In alternating OLO, a learner at each round t ∈[n] selects a vector xt and then an adversary selects a cost-vector ct ∈[−1,1]n. ...

2023

Validating Automatic Speech Recognition and Understanding for Pre-Filling Radar Labels-Increasing Safety While Reducing Air Traffic Controllers' Workload

Juan Pablo Zuluaga Gomez

Automatic speech recognition and understanding (ASRU) for air traffic control (ATC) has been investigated in different ATC environments and applications. The objective of this study was to quantify the effect of ASRU support for air traffic controllers (AT ...

2023

Knowledge Distillation for 6D Pose Estimation by Aligning Distributions of Local Predictions

Mathieu Salzmann, Yinlin Hu, Shuxuan Guo

Knowledge distillation facilitates the training of a compact student network by using a deep teacher one. While this has achieved great success in many tasks, it remains completely unstudied for image-based 6D object pose estimation. In this work, we intro ...

Los Alamitos2023

Social Learning with Disparate Hypotheses

Ali H. Sayed, Stefan Vlaski, Virginia Bordignon, Konstantinos Ntemos

In this paper we study the problem of social learning under multiple true hypotheses and self-interested agents. In this setup, each agent receives data that might be generated from a different hypothesis (or state) than the data other agents receive. In c ...

IEEE2022

Self-Exciting Point Processes: Identification and Control

Michael Mark

This thesis addresses theoretical and practical aspects of identification and subsequent control of self-exciting point processes. The main contributions correspond to four separate scientific papers.In the first paper, we address the challenge of robust i ...

EPFL2022

A note on universal inference

Anthony Christopher Davison, Timmy Rong Tian Tse

Universal inference enables the construction of confidence intervals and tests without regularity conditions by splitting the data into two parts and appealing to Markov's inequality. Previous investigations have shown that the cost of this generality is a ...

WILEY2022

Identifiability and Generalizability from Multiple Experts in Inverse Reinforcement Learning

Volkan Cevher, Paul Thierry Yves Rolland, Luca Viano, Boris Nikolov

While Reinforcement Learning (RL) aims to train an agent from a reward function in a given environment, Inverse Reinforcement Learning (IRL) seeks to recover the reward function from observing an expert’s behavior. It is well known that, in general, variou ...

2022

Stochastic Second-Order Methods Improve Best-Known Sample Complexity of SGD for Gradient-Dominated Function

Patrick Thiran, Negar Kiyavash, Saber Salehkaleybar

We study the performance of Stochastic Cubic Regularized Newton (SCRN) on a class of functions satisfying gradient dominance property with

1\le\alpha\le2

which holds in a wide range of applications in machine learning and signal processing. This conditio ...

NeurIPS2022

Metrizing Fairness

Daniel Kuhn, Yves Rychener, Bahar Taskesen

We study supervised learning problems for predicting properties of individuals who belong to one of two demographic groups, and we seek predictors that are fair according to statistical parity. This means that the distributions of the predictions within th ...

2022

Ensembles for sequence learning

Graph Chatbot

Chat with Graph Search

SKA Science Data Challenge 2: analysis and results

Alternation makes the adversary weaker in two-player games

Validating Automatic Speech Recognition and Understanding for Pre-Filling Radar Labels-Increasing Safety While Reducing Air Traffic Controllers' Workload

Knowledge Distillation for 6D Pose Estimation by Aligning Distributions of Local Predictions

Social Learning with Disparate Hypotheses

Self-Exciting Point Processes: Identification and Control

A note on universal inference

Identifiability and Generalizability from Multiple Experts in Inverse Reinforcement Learning

Stochastic Second-Order Methods Improve Best-Known Sample Complexity of SGD for Gradient-Dominated Function

Metrizing Fairness

SKA Science Data Challenge 2: analysis and results

Alternation makes the adversary weaker in two-player games

Validating Automatic Speech Recognition and Understanding for Pre-Filling Radar Labels-Increasing Safety While Reducing Air Traffic Controllers' Workload

Self-Exciting Point Processes: Identification and Control

A note on universal inference

Stochastic Second-Order Methods Improve Best-Known Sample Complexity of SGD for Gradient-Dominated Function

Metrizing Fairness

Knowledge Distillation for 6D Pose Estimation by Aligning Distributions of Local Predictions

Social Learning with Disparate Hypotheses

Identifiability and Generalizability from Multiple Experts in Inverse Reinforcement Learning