Unit

Effective Altruism Lausanne

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Related publications (30)

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Machine Learning for Modeling Stock Returns

Teng Andrea Xu

Throughout history, the pace of knowledge and information sharing has evolved into an unthinkable speed and media. At the end of the XVII century, in Europe, the ideas that would shape the "Age of Enlightenment" were slowly being developed in coffeehouses, ...

EPFL2024

Breaking the Curse of Dimensionality in Deep Neural Networks by Learning Invariant Representations

Leonardo Petrini

Artificial intelligence, particularly the subfield of machine learning, has seen a paradigm shift towards data-driven models that learn from and adapt to data. This has resulted in unprecedented advancements in various domains such as natural language proc ...

EPFL2023

Hyperdimensional computing for biosignal monitoring: Applications for epilepsy detection

Una Pale

Hyperdimensional (HD) computing is a novel approach to machine learning inspired by neuroscience, which uses vectors in a hyper-dimensional space to represent data and models. This approach has gained significant interest in recent years with applications ...

EPFL2023

Mechanical intelligence for learning embodied sensor-object relationships

Ahalya Prabhakar

Intelligence involves processing sensory experiences into representations useful for prediction. Understanding sensory experiences and building these contextual representations without prior knowledge of sensor models and environment is a challenging unsup ...

NATURE PORTFOLIO2022

Motion Style Transfer: Modular Low-Rank Adaptation for Deep Motion Forecasting

Alexandre Massoud Alahi, Yuejiang Liu, Parth Ashit Kothari, Danya Li

Deep motion forecasting models have achieved great success when trained on a massive amount of data. Yet, they often perform poorly when training data is limited. To address this challenge, we propose a transfer learning approach for efficiently adapting p ...

2022

Lifelong Machine Learning with Data Efficiency and Knowledge Retention

Fei Mi

Artificial intelligence (AI) and machine learning (ML) have become de facto tools in many real-life applications to offer a wide range of benefits for individuals and our society. A classic ML model is typically trained with a large-scale static dataset in ...

EPFL2021

Loss landscape and symmetries in Neural Networks

Mario Geiger

Neural networks (NNs) have been very successful in a variety of tasks ranging from machine translation to image classification. Despite their success, the reasons for their performance are still not well-understood. This thesis explores two main themes: lo ...

EPFL2021

The organisation of science: topics, incentives and funding.

Omar Ballester Gonzalez

Ever since the links between the development of new technologies and economic growth became evident, researchers have attempted to study how the creation of knowledge fosters progress. If pushing the frontier of knowledge has an impact on progress and well ...

EPFL2020

Improving speech embedding using crossmodal transfer learning with audio-visual data

Jean-Marc Odobez

Learning a discriminative voice embedding allows speaker turns to be compared directly and efficiently, which is crucial for tasks such as diarization and verification. This paper investigates several transfer learning approaches to improve a voice embeddi ...

2019

Getting looped in to the web: characterizing learning processes and educational responses

Through profiling and matching processes, technology provides individuals with information that becomes redundant to their previous beliefs, attitudes and preferences. The emergence of informational redundancies encouraged by some technologies is likely to ...

2017