output
20112026
most citedOptimization Problems for Machine Learning: A Survey

373 citations

Showing 2025Show all

6 papers · 1 filter

cs.LG2025★ 3 cited

Underrepresentation, Label Bias, and Proxies: Towards Data Bias Profiles for the EU AI Act and Beyond

Marina Ceccon, Giandomenico Cornacchia, Davide Dalle Pezze +2

Undesirable biases encoded in the data are key drivers of algorithmic discrimination. Their importance is widely recognized in the algorithmic fairness literature, as well as legis…

cs.CL2025

A Position Paper on the Automatic Generation of Machine Learning Leaderboards

Roelien C Timmer, Yufang Hou, Stephen Wan

An important task in machine learning (ML) research is comparing prior work, which is often performed via ML leaderboards: a tabular overview of experiments with comparable conditi…

cs.AI2025★ 6 cited

Open and Sustainable AI: challenges, opportunities and the road ahead in the life sciences (October 2025 -- Version 2)

Gavin Farrell, Eleni Adamidi, Rafael Andrade Buono +27

Artificial intelligence (AI) has recently seen transformative breakthroughs in the life sciences, expanding possibilities for researchers to interpret biological information at an…

quant-ph2025★ 2 cited

Quantum Optimization Benchmarking Library - The Intractable Decathlon

Thorsten Koch, David E. Bernal Neira, Ying Chen +24

Through recent progress in hardware development, quantum computers have advanced to the point where benchmarking of (heuristic) quantum algorithms at scale is within reach. Particu…

quant-ph2025★ 1 cited

Realization of Two-dimensional Discrete Time Crystals with Anisotropic Heisenberg Coupling

Eric D. Switzer, Niall Robertson, Nathan Keenan +7

A discrete time crystal (DTC) is the paradigmatic example of a phase of matter that occurs exclusively in systems out of equilibrium. This phenomenon is characterized by the sponta…

stat.ME2025★ 2 cited

Doubly-Robust Functional Average Treatment Effect Estimation

Lorenzo Testa, Tobia Boschi, Francesca Chiaromonte +2

Understanding causal relationships in the presence of complex, structured data remains a central challenge in modern statistics and science in general. While traditional causal inf…