Publications associées à The Power of Decision Trees for Composition and Search Problems

Publications associées (15)

Guaranteed Yet Hard to Find: Uncovering FPGA Routing Convergence Paradox

Mirjana Stojilovic, Shashwat Shrivastava

Routing is one of the major challenges of FPGA compilation. PathFinder is a ubiquitous FPGA routing algorithm used in industry and academia due to its ability to adapt to arbitrary routing architectures and user circuits. However, to this day, we do not fu ...

IEEE2025

Optimizing fairness and utility in healthcare machine learning models

Gökhan Özbulak

Demographic fairness or equity is a crucial aspect of machine learning models, particularly in critical domains such as healthcare, where errors can have severe consequences. A fair model avoids making distinctions between groups with different sensitive o ...

2025

Toward Autonomous Laser Manufacturing: Solving Key Challenges in Optimization, Monitoring, and Control

Giulio Masinelli

Laser material processing (LMP) has revolutionized modern manufacturing, emerging as a cornerstone technology valued for its precision, speed, and versatility, especially in high-stakes sectors like aerospace, automotive, and medical device production. Des ...

EPFL2025

Reach For the Arcs: Reconstructing Surfaces from SDFs via Tangent Points

Yingying Ren

We introduce an algorithm to reconstruct a mesh from discrete samples of a shape's Signed Distance Function (SDF). A simple geometric reinterpretation of the SDF lets us formulate the problem through a point cloud, from which a surface can be extracted wit ...

Association for Computing Machinery2024

Theory and applications of the sum-of-squares technique

Luca Pesce, Giovanni Piccioli, Elisabetta Cornacchia

The sum-of-squares (SOS) approximation method is a technique used in optimization problems to derive lower bounds on the optimal value of an objective function. By representing the objective function as a sum of squares in a feature space, the SOS method t ...

2024

Neural Redshift: Random Networks are not Random Functions

Valentin Hartmann

Our understanding of the generalization capabilities of neural networks (NNs) is still incomplete. Prevailing explanations are based on implicit biases of gradient descent (GD) but they cannot account for the capabilities of models from gradient-free metho ...

IEEE2024

Validating functional redundancy with mixed generative adversarial networks

Quoc Viet Hung Nguyen, Thành Tâm Nguyên, Thanh Trung Huynh

Data redundancy has been one of the most important problems in data-intensive applications such as data mining and machine learning. Removing data redundancy brings many benefits in efficient data updating, effective data storage, and error-free query proc ...

ELSEVIER2023

Reed-Muller Codes

Emmanuel Abbé

Reed-Muller (RM) codes are among the oldest, simplest and perhaps most ubiquitous family of codes. They are used in many areas of coding theory in both electrical engineering and computer science. Yet, many of their important properties are still under inv ...

Emerald2023

Low-Rank Tensor Methods for High-Dimensional Problems

Christoph Max Strössner

In this thesis, we propose and analyze novel numerical algorithms for solving three different high-dimensional problems involving tensors. The commonality of these problems is that the tensors can potentially be well approximated in low-rank formats. Ident ...

EPFL2023

On Approximations of Data-Driven Chance Constrained Programs over Wasserstein Balls

Daniel Kuhn, Wolfram Wiesemann

Distributionally robust chance constrained programs minimize a deterministic cost function subject to the satisfaction of one or more safety conditions with high probability, given that the probability distribution of the uncertain problem parameters affec ...

2023

Covering Convex Bodies and the Closest Vector Problem

Moritz Andreas Venzin, Márton Naszódi

We present algorithms for the (1+epsilon)-approximate version of the closest vector problem for certain norms. The currently fastest algorithm (Dadush and Kun 2016) for general norms in dimension n has running time of 2(O(n)) (1/epsilon)(n) . We improve th ...

2022

Post-Quantum Succinct Arguments: Breaking the Quantum Rewinding Barrier

Alessandro Chiesa

We prove that Kilian's four-message succinct argument system is post-quantum secure in the standard model when instantiated with any probabilistically checkable proof and any collapsing hash function (which in turn exist based on the post-quantum hardness ...

IEEE COMPUTER SOC2022

Hyperdimensional computing for blind and one-shot classification of EEG error-related potentials

José del Rocio Millán Ruiz

The mathematical properties of high-dimensional (HD) spaces show remarkable agreement with behaviors controlled by the brain. Computing with HD vectors, referred to as “hypervectors,” is a brain-inspired alternative to computing with numbers. HD computing ...

Springer Verlag2020

Too Many Materials and Too Many Applications: An Experimental Problem Waiting for a Computational Solution

Berend Smit, Daniele Ongari, Christoph Leopold Talirz

Finding the best material for a specific application is the ultimate goal of materials discovery. However, there is also the reverse problem: when experimental groups discover a new material, they would like to know all the possible applications this mater ...

AMER CHEMICAL SOC2020

Image Clustering Algorithms to Identify Complicated Cerebral Diseases. Description and Comparison

Maria-Alexandra Paun

This article presents two algorithms developed based on two different techniques, from clusterization theory, namely k-means clustering technique and Fuzzy C-means technique, respectively. In this context, the study offers a sustained comparison of the two ...

2020