Publications associées à Recherche empirique

SIMPLE HIERARCHICAL PLANNING WITH DIFFUSION

Diffusion-based generative methods have proven effective in modeling trajectories with offline datasets. However, they often face computational challenges and can falter in generalization, especially in capturing temporal abstractions for long- horizon tas ...

2024

Touch and Closeness in Naturally Organized Activities

Countless aspects of touch and closeness have been questioned in an unprecedented way during the recent Covid epidemic. Social practices as banal as greetings were both reflexively and practically challenged and sometimes deeply altered, resulting in painf ...

2024

Data-Driven Music Theory: Curating and Investigating Large Corpora of Digitally Encoded Music Analyses

Johannes Hentschel

This dissertation on data-driven music theory is centered around curatorial practices concerning the creation, publication, and evaluation of large, expert-annotated symbolic datasets. With its primary interest in the harmony of European tonal music from i ...

EPFL2024

The impact of different methods of increasing the intensity of compassion in engineering ethics cases

Roland John Tormey, Nihat Kotluk

Despite the growing interest in emotions in engineering education, empirical research on incorporating them into engineering ethics education is limited. Therefore, we designed this experimental study to assess how different methods for integrating compass ...

2024

A hybrid microscopic model for multimodal traffic with empirical observations from aerial footage

Nikolaos Geroliminis, Georgios Anagnostopoulos

Microscopic traffic flow models can be distinguished in lane-based or lane-free depending on the degree of lane-discipline. This distinction holds true only if motorcycles are neglected in lane-based traffic. In cities, as opposed to highways, this is an o ...

2023

Reliable strategies for implementing model-based navigation on fixed-wing drones

Jan Skaloud, Gabriel François Laupré, Lucas Pirlet

A relatively novel approach of autonomous navigation employing platform dynamics as the primary process model raises new implementational challenges. These are related to: (i) potential numerical instabilities during longer flights; (ii) the quality of mod ...

2023

Robust Distributed Learning: Tight Error Bounds and Breakdown Point under Data Heterogeneity

Rachid Guerraoui, Youssef Allouah, Geovani Rizk, Nirupam Gupta, Rafaël Benjamin Pinot

The theory underlying robust distributed learning algorithms, designed to resist adversarial machines, matches empirical observations when data is homogeneous. Under data heterogeneity however, which is the norm in practical scenarios, established lower bo ...

2023

Beyond Spectral Gap: The Role of the Topology in Decentralized Learning

Martin Jaggi, Thijs Vogels, Hadrien Hendrikx

In data-parallel optimization of machine learning models, workers collaborate to improve their estimates of the model: more accurate gradients allow them to use larger learning rates and optimize faster. In the decentralized setting, in which workers commu ...

Microtome Publishing2023

When do Minimax-fair Learning and Empirical Risk Minimization Coincide?

Volkan Cevher

Minimax-fair machine learning minimizes the error for the worst-off group. However, empirical evidence suggests that when sophisticated models are trained with standard empirical risk minimization (ERM), they often have the same performance on the worst-of ...

2023

An Annotated Corpus of Tonal Piano Music from the Long 19th Century

Martin Alois Rohrmeier, Fabian Claude Moss, Johannes Hentschel, Markus Franz Josef Neuwirth

We present a dataset of 264 annotated piano pieces of nine composers, composed in the long 19th century (https://doi.org/10.5281/zenodo.7483349). Annotations adhere to the DCML harmony annotation standard and include Roman numerals, phrase boundaries, and ...

Ohio State Univ, Sch Music2023