Publications related to AN l(p) THEORY OF PCA AND SPECTRAL CLUSTERING

Related publications (10)

Relatively Robust Economic Order Quantity with Optimal Laplacian Confidence Intervals

The parameters for determining the economic order quantity (EOQ) are often not well known or may change between order cycles in an unpredictable manner. We propose a distribution-free method to determine a relatively robust EOQ that guarantees optimal cost ...

IEEE2025

Gaussian universality of perceptrons with random labels

Lenka Zdeborová, Florent Gérard Krzakala, Bruno Loureiro, Ludovic Théo Stephan, Federica Gerace

While classical in many theoretical settings-and in particular in statistical physics-inspired works-the assumption of Gaussian i.i.d. input data is often perceived as a strong limitation in the context of statistics and machine learning. In this study, we ...

Amer Physical Soc2024

The Benefits of Reusing Batches for Gradient Descent in Two-Layer Networks: Breaking the Curse of Information and Leap Exponents

Lenka Zdeborová, Florent Gérard Krzakala, Yatin Dandi, Emanuele Troiani, Luca Pesce, Luca Arnaboldi

We investigate the training dynamics of two-layer neural networks when learning multi-index target functions. We focus on multi-pass gradient descent (GD) that reuses the batches multiple times and show that it significantly changes the conclusion about wh ...

JMLR2024

Towards a classification of the building stock in terms of potential energy savings through advanced control

Matthias Heinrich

Developing advanced control strategies is a relevant pathway to achieve energy savings in heating, ventilation, and air conditioning systems. Nevertheless, the studies presenting these controls usually quantify the potential energy savings by analysing a s ...

Elsevier BV2024

Optimal Convex Lifted Sparse Phase Retrieval and PCA With an Atomic Matrix Norm Regularizer

Andrew Duncan Mc Rae

We present novel analysis and algorithms for solving sparse phase retrieval and sparse principal component analysis (PCA) with convex lifted matrix formulations. The key innovation is a new mixed atomic matrix norm that, when used as regularization, promot ...

2023

Disagreement and fragmentation in growing groups

Jiyong Zhang, Yubo Xie

The arise of disagreement is an emergent phenomenon that can be observed within a growing social group and, beyond a certain threshold, can lead to group fragmentation. To better understand how disagreement emerges, we introduce an analytically tractable m ...

PERGAMON-ELSEVIER SCIENCE LTD2023

A Simple LP-Based Approximation Algorithm for the Matching Augmentation Problem

Ola Nils Anders Svensson, Etienne Michel François Bamas, Marina Rebekah Rosie Drygala

The Matching Augmentation Problem (MAP) has recently received significant attention as an important step towards better approximation algorithms for finding cheap 2-edge connected subgraphs. This has culminated in a 5/3-approximation algorithm. However, th ...

SPRINGER INTERNATIONAL PUBLISHING AG2022

Deep learning-based galaxy image deconvolution

Frédéric Courbin, Pascale Jablonka, Utsav Akhaury

With the onset of large-scale astronomical surveys capturing millions of images, there is an increasing need to develop fast and accurate deconvolution algorithms that generalize well to different images. A powerful and accessible deconvolution method woul ...

FRONTIERS MEDIA SA2022

Non-Structured DNN Weight Pruning--Is It Beneficial in Any Platform?

Shaokai Ye

Large deep neural network (DNN) models pose the key challenge to energy efficiency due to the significantly higher energy consumption of off-chip DRAM accesses than arithmetic or SRAM operations. It motivates the intensive research on model compression wit ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2022

Uncertain Sampling with Certain Priors

Golnooshsadat Elhami

Sampling has always been at the heart of signal processing providing a bridge between the analogue world and discrete representations of it, as our ability to process data in continuous space is quite limited. Furthermore, sampling plays a key part in unde ...

EPFL2021