Malik Tiomoko

Researcher, Huawei Technologies Ltd.

Joined

July 2019

Names

Malik Tiomoko

Emails

****@u-psud.fr (Confirmed)

****@yahoo.fr (Confirmed)

****@huawei.com (Confirmed)

Personal Links

DBLP

Career & Education History

Researcher

Huawei Technologies Ltd. (huawei.com)

2021 – Present

PhD student

UPSud/INRIA University Paris-Saclay (u-psud.fr)

2018 – 2021

Advisors, Relations & Conflicts

PhD Advisor

Romain COUILLET

2018 – 2021

Expertise

Transfer Learning

2018 – 2021

Random Matrix Theory

2018 – 2021

Multi Task Learning

2018 – 2021

Publications

High-Dimensional Analysis of Bootstrap Ensemble Classifiers
Malik Tiomoko, Hamza Cherkaoui, Mohamed El Amine Seddik, Cosme Louart, Ekkehard Schnoor, Balázs Kégl
- AISTATS 2026 Poster
- Readers: Everyone
Human-in-the-Loop Adaptive Optimization for Improved Time Series Forecasting
Malik Tiomoko, Hamza Cherkaoui, Giuseppe Paolo, Yili Zhang, Yu Meng, Zhang Keli, Hafiz Tiomoko Ali
- Submitted to ICLR 2026
- Readers: Everyone
LLMs as In-Context Meta-Learners for Model and Hyperparameter Selection
Youssef Attia El Hili, Albert Thomas, Malik Tiomoko, Abdelhakim Benechehab, Corentin Léger, Corinne Ancourt, Balázs Kégl
- Submitted to ICLR 2026
- Readers: Everyone
Mantis: Lightweight Calibrated Foundation Model for User-Friendly Time Series Classification
Vasilii Feofanov, Marius Alonso, Songkang Wen, Romain Ilbert, Hongbo Guo, Malik Tiomoko, Lujia Pan, Jianfeng Zhang, Ievgen Redko
- FMSD @ ICML 2025
- Readers: Everyone
INSTRUCTION-FOLLOWING LLMS FOR TIME SERIES PREDICTION: A TWO-STAGE MULTIMODAL APPROACH
Yu Meng, Malik Tiomoko
- Submitted to ICLR 2025
- Readers: Everyone
Enhancing Multivariate Time Series Forecasting via Multi-Task Learning and Random Matrix Theory
Romain Ilbert, Malik Tiomoko, Cosme Louart, Vasilii Feofanov, Themis Palpanas, Ievgen Redko
- NeurIPS 2024 TSALM Workshop
- Readers: Everyone
Analysing Multi-Task Regression via Random Matrix Theory with Application to Time Series Forecasting
Romain Ilbert, Malik Tiomoko, Cosme Louart, Ambroise Odonnat, Vasilii Feofanov, Themis Palpanas, Ievgen Redko
- NeurIPS 2024 spotlight
- Readers: Everyone
Random matrix theory improved Fréchet mean of symmetric positive definite matrices
Florent Bouchard, Ammar Mian, Malik Tiomoko, Guillaume Ginolhac, Frederic Pascal
- ICML 2024 Poster
- Readers: Everyone
Learning from Low Rank Tensor Data: A Random Tensor Theory Perspective
Mohamed El Amine Seddik, Malik Tiomoko, Alexis Decurninge, Maxim Panov, Maxime Guillaud
- Published: 08 May 2023, Last Modified: 26 Jun 2023
- UAI 2023
- Readers: Everyone
Random Matrix Analysis to Balance between Supervised and Unsupervised Learning under the Low Density Separation Assumption
Vasilii Feofanov, Malik Tiomoko, Aladin Virmaux
- ICML 2023 Poster
- Readers: Everyone

View all 21 publications

Co-Authors

View all 38 co-authors