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Albert Senen-Cerda

6 papers hereh-index 446 citations6 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • first author2
  • middle author1
  • last author3

Across the 6 of 6 papers where every author was matched, so the position is known.

fields
  • cs.LG4
  • math.OC1
  • math.PR1
same name
  • Albert Senen-Cerda — 1 paper, h 0

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

activity
20202023
most citedUniversal Approximation in Dropout Neural Networks

11 citations · 18 across the 6 of their papers we have counts for

collaborators
Showing cs.LGShow all

4 papers · 1 filter

cs.LG2023

Score-Aware Policy-Gradient and Performance Guarantees using Local Lyapunov Stability

Céline Comte, Matthieu Jonckheere, Jaron Sanders +1

In this paper, we introduce a policy-gradient method for model-based reinforcement learning (RL) that exploits a type of stationary distributions commonly obtained from Markov deci…

cs.LG2022

Detection and Evaluation of Clusters within Sequential Data

Alexander Van Werde, Albert Senen-Cerda, Gianluca Kosmella +1

Sequential data is ubiquitous -- it is routinely gathered to gain insights into complex processes such as behavioral, biological, or physical processes. Challengingly, such data no…

cs.LG2020★ 11 cited

Universal Approximation in Dropout Neural Networks

Oxana A. Manita, Mark A. Peletier, Jacobus W. Portegies +2

We prove two universal approximation theorems for a range of dropout neural networks. These are feed-forward neural networks in which each edge is given a random {0,1}-valued f…

cs.LG2020

Asymptotic convergence rate of Dropout on shallow linear neural networks

Albert Senen-Cerda, Jaron Sanders

We analyze the convergence rate of gradient flows on objective functions induced by Dropout and Dropconnect, when applying them to shallow linear Neural Networks (NNs) - which can…

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