Nicolò Colombo

According to our database, Nicolò Colombo authored at least 21 papers between 2014 and 2024.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2024

State-space models can learn in-context by gradient descent.

Neeraj Mohan Sushma, Yudou Tian, Harshvardhan Mestha, Nicolò Colombo, David Kappel, Anand Subramoney

CoRR, 2024

Entropy Reweighted Conformal Classification.

Rui Luo, Nicolò Colombo

CoRR, 2024

Conformal Load Prediction with Transductive Graph Autoencoders.

Rui Luo, Nicolò Colombo

CoRR, 2024

Structured Learning of Compositional Sequential Interventions.

Jialin Yu, Andreas Koukorinis, Nicolò Colombo, Yuchen Zhu, Ricardo Silva

CoRR, 2024

Normalizing Flows for Conformal Regression.

Nicolò Colombo

CoRR, 2024

2023

On training locally adaptive CP.

Nicolò Colombo

Proceedings of the Conformal and Probabilistic Prediction with Applications, 2023

2021

Differentiable Architecture Pruning for Transfer Learning.

Nicolò Colombo, Yang Gao

CoRR, 2021

Adapting by Pruning: A Case Study on BERT.

Yang Gao, Nicolò Colombo, Wei Wang

CoRR, 2021

2020

Disentangling Neural Architectures and Weights: A Case Study in Supervised Classification.

Nicolò Colombo, Yang Gao

CoRR, 2020

Multiple Metric Learning for Structured Data.

Nicolò Colombo

CoRR, 2020

Training conformal predictors.

Nicolò Colombo, Vladimir Vovk

Proceedings of the Conformal and Probabilistic Prediction and Applications, 2020

2019

Counterfactual Distribution Regression for Structured Inference.

Nicolò Colombo, Ricardo Silva, Soong Moon Kang, Arthur Gretton

CoRR, 2019

2018

Bayesian Semi-supervised Learning with Graph Gaussian Processes.

Yin Cheng Ng, Nicolò Colombo, Ricardo Silva

Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

2017

Tomography of the London Underground: a Scalable Model for Origin-Destination Data.

Nicolò Colombo, Ricardo Silva, Soong Moon Kang

Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

Experimental design trade-offs for gene regulatory network inference: An in silico study of the yeast Saccharomyces cerevisiae cell cycle.

Johan Markdahl, Nicolò Colombo, Johan Thunberg, Jorge M. Gonçalves

Proceedings of the 56th IEEE Annual Conference on Decision and Control, 2017

2016

Approximate Joint Matrix Triangularization.

Nicolò Colombo, Nikos Vlassis

CoRR, 2016

A posteriori error bounds for joint matrix decomposition problems.

Nicolò Colombo, Nikos Vlassis

Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

Tensor Decomposition via Joint Matrix Schur Decomposition.

Nicolò Colombo, Nikos Vlassis

Proceedings of the 33nd International Conference on Machine Learning, 2016

2015

FastMotif: spectral sequence motif discovery.

Nicolò Colombo, Nikos Vlassis

Bioinform., 2015

Stable Spectral Learning Based on Schur Decomposition.

Nicolò Colombo, Nikos Vlassis

Proceedings of the Thirty-First Conference on Uncertainty in Artificial Intelligence, 2015

2014

Spectral Sequence Motif Discovery.

Nicolò Colombo, Nikos Vlassis

CoRR, 2014