Victor Storchan

According to our database, Victor Storchan authored at least 11 papers between 2019 and 2024.

Collaborative distances:

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

2024

Towards a Framework for Openness in Foundation Models: Proceedings from the Columbia Convening on Openness in Artificial Intelligence.

Adrien Basdevant, Camille François, Victor Storchan, Kevin Bankston, Ayah Bdeir, Brian Behlendorf, Mérouane Debbah, Sayash Kapoor, Yann LeCun, Mark Surman, Helen King-Turvey, Nathan Lambert, Stefano Maffulli, Nik Marda, Govind Shivkumar, Justine Tunney

CoRR, 2024

On the Societal Impact of Open Foundation Models.

Sayash Kapoor, Rishi Bommasani, Kevin Klyman, Shayne Longpre, Ashwin Ramaswami, Peter Cihon, Aspen K. Hopkins, Kevin Bankston, Stella Biderman, Miranda Bogen, Rumman Chowdhury, Alex Engler, Peter Henderson, Yacine Jernite, Seth Lazar, Stefano Maffulli, Alondra Nelson, Joelle Pineau, Aviya Skowron, Dawn Song, Victor Storchan, Daniel Zhang, Daniel E. Ho, Percy Liang, Arvind Narayanan

CoRR, 2024

Position: On the Societal Impact of Open Foundation Models.

Sayash Kapoor, Rishi Bommasani, Kevin Klyman, Shayne Longpre, Ashwin Ramaswami, Peter Cihon, Aspen K. Hopkins, Kevin Bankston, Stella Biderman, Miranda Bogen, Rumman Chowdhury, Alex Engler, Peter Henderson, Yacine Jernite, Seth Lazar, Stefano Maffulli, Alondra Nelson, Joelle Pineau, Aviya Skowron, Dawn Song, Victor Storchan, Daniel Zhang, Daniel E. Ho, Percy Liang, Arvind Narayanan

Proceedings of the Forty-first International Conference on Machine Learning, 2024

2023

Transductive Learning for Textual Few-Shot Classification in API-based Embedding Models.

Pierre Colombo, Victor Pellegrain, Malik Boudiaf, Victor Storchan, Myriam Tami, Ismail Ben Ayed, Céline Hudelot, Pablo Piantanida

CoRR, 2023

Transductive Learning for Textual Few-Shot Classification in API-based Embedding Models.

Pierre Colombo, Victor Pellegrain, Malik Boudiaf, Myriam Tami, Victor Storchan, Ismail Ben Ayed, Pablo Piantanida

Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing, 2023

2021

Beyond Fairness Metrics: Roadblocks and Challenges for Ethical AI in Practice.

Jiahao Chen, Victor Storchan, Eren Kurshan

CoRR, 2021

Seven challenges for harmonizing explainability requirements.

Jiahao Chen, Victor Storchan

CoRR, 2021

Learning who is in the market from time series: market participant discovery through adversarial calibration of multi-agent simulators.

Victor Storchan, Svitlana Vyetrenko, Tucker Balch

CoRR, 2021

On the current and emerging challenges of developing fair and ethical AI solutions in financial services.

Eren Kurshan, Jiahao Chen, Victor Storchan, Hongda Shen

Proceedings of the ICAIF'21: 2nd ACM International Conference on AI in Finance, Virtual Event, November 3, 2021

2020

Explainable clustering and application to wealth management compliance.

Enguerrand Horel, Kay Giesecke, Victor Storchan, Naren Chittar

Proceedings of the ICAIF '20: The First ACM International Conference on AI in Finance, 2020

2019

Data Augmentation via Adversarial Networks for Optical Character Recognition/Conference Submissions.

Victor Storchan

Proceedings of the 2019 International Conference on Document Analysis and Recognition, 2019