Ricardo Silva

According to our database, Ricardo Silva authored at least 13 papers between 2017 and 2024.

Collaborative distances:

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

2024

Dual Risk Minimization: Towards Next-Level Robustness in Fine-tuning Zero-Shot Models.

Kaican Li, Weiyan Xie, Yongxiang Huang, Didan Deng, Lanqing Hong, Zhenguo Li, Ricardo Silva, Nevin L. Zhang

CoRR, 2024

Fine-Tuning Pre-trained Language Models for Robust Causal Representation Learning.

Jialin Yu, Yuxiang Zhou, Yulan He, Nevin L. Zhang, Ricardo Silva

CoRR, 2024

Structured Learning of Compositional Sequential Interventions.

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

CoRR, 2024

2022

Neural Network Approximation of Graph Fourier Transform for Sparse Sampling of Networked Dynamics.

Alessio Pagani, Zhuangkun Wei, Ricardo Silva, Weisi Guo

ACM Trans. Internet Techn., 2022

Graph and tensor-train recurrent neural networks for high-dimensional models of limit order books.

Jacobo Roa-Vicens, Yao Lei Xu, Ricardo Silva, Danilo P. Mandic

Proceedings of the 3rd ACM International Conference on AI in Finance, 2022

2020

Neural Network Approximation of Graph Fourier Transforms for Sparse Sampling of Networked Flow Dynamics.

Alessio Pagani, Zhuangkun Wei, Ricardo Silva, Weisi Guo

CoRR, 2020

2019

Adversarial recovery of agent rewards from latent spaces of the limit order book.

Jacobo Roa-Vicens, Yuanbo Wang, Virgile Mison, Yarin Gal, Ricardo Silva

CoRR, 2019

Counterfactual Distribution Regression for Structured Inference.

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

CoRR, 2019

Towards Inverse Reinforcement Learning for Limit Order Book Dynamics.

Jacobo Roa-Vicens, Cyrine Chtourou, Angelos Filos, Francisco Rullan, Yarin Gal, Ricardo Silva

CoRR, 2019

2018

Visualizing a Team's Goal Chances in Soccer from Attacking Events: A Bayesian Inference Approach.

Gavin A. Whitaker, Ricardo Silva, Daniel Edwards

Big Data, 2018

2017

Causality.

Ricardo Silva

Proceedings of the Encyclopedia of Machine Learning and Data Mining, 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

Visualization of Topic-Sentiment Dynamics in Crowdfunding Projects.

Rafael Augusto Ferreira do Carmo, Soong Moon Kang, Ricardo Silva

Proceedings of the Advances in Intelligent Data Analysis XVI, 2017