About
I am a second year PhD student at
Mila and DIRO under the supervision of
Simon Lacoste-Julien.
I am interested in constrained optimization for deep learning. I am
working on how to reliably solve constrained optimization problems with
some of the following characteristics: non-convexity, non-smoothness,
non-differentiability, stochastic constraints, and large numbers of
constraints.
Check out Cooper, a library for constrained optimization in Pytorch that I co-founded.
Previously, I was an intern at Simon's group at Mila under the
supervision of Jose Gallego-Posada.
Before that, I graduated from the BSc in Mathematical Engineer at
Universidad EAFIT. During the BSc, I spent a
summer at McKinsey & Co. as a research intern.
Research interests: (Non-Convex) Constrained Optimization, Min-Max Optimization, Deep Learning, Sparsity, Fairness.
Contact: juan43ramirez (at) gmail (dot) com
News
2024
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Mar 04: Delighted to receive Université de Montréal's AI scholarship 2023-2024!
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Jan 29: Excited to be a TA at the first edition of the Tropical Probabilistic AI School in Rio de Janeiro, Brazil! I am happy to see more AI events popping up in Latin America.
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Jan 16:
Balancing Act: Constraining Disparate Impact in Sparse Models has been accepted at ICLR 2024! Vienna, here we come.
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Jan 12: Quentin Bertrand and I will be TAing Gauthier Gidel's Adversarial Machine Learning course at Mila and the University of Montreal.
2023
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Dec 7: Excited to give a talk at Montréal Machine Learning and Optimization (MTL MLOpt) about our recent work Balancing Act: Constraining Disparate Impact in Sparse Models.
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Sep 4: Together with António Góis, I will be TAing Simon Lacoste-Julien's graduate course on Probabilistic Graphical Models at Mila.
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Jul 23: Arriving in Honolulu, Hawaii, where I will have the pleasure to present Omega: Optimistic EMA Gradients. Omega, our method for stochastic min-max optimization, was awarded an oral at the LatinX in AI workshop at ICML 2023!
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Jan 27: I will attend Khipu 2023 in Montevideo, Uruguay. Glad to be a part of the Latin American AI community.
2022
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Oct 14: See you at the Pytorch conference 2022 in New Orleans! Cooper will be making an appearance (poster).
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Sep 14: I will be presenting my first NeurIPS paper: Controlled Sparsity via Constrained Optimization or: How I Learned to Stop Tuning Penalties and Love Constraints in New Orleans.
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Sep 05: Excited to start a PhD in Artificial Intelligence under the supervision of Simon Lacoste-Julien at Mila and the University of Montreal.
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Jul 25: Taking part in CIFAR's Deep Learning Reinforcement Learning Summer School.
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Jul 8: Attending the Sparsity in Neural Networks workshop. We are presenting our latest work on implicit neural representations: L0onie: Compressing COINs with L0-constraints.
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Mar 15: We have released Cooper: a library for Lagrangian-based constrained optimization in Pytorch.
Previous
2021
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Dec 17:
Flexible Learning of Sparse Neural Networks via Constrained L0 Regularization,
won the best poster award at the LatinX in AI Workshop @ NeurIPS 2021!
-
Nov 1: Starting an internship at Mila,
a fundamental machine learning research lab. I will join
Simon Lacoste-Julien's
group under the supervision of
Jose Gallego-Posada.
-
Oct 22:
My first ever paper,
Flexible Learning of Sparse Neural Networks via Constrained L0 Regularization,
has been accepted at the LatinX in AI Workshop at NeurIPS 2021!
-
Aug 2:
during the next three weeks, I will attend (virtually)
Neuromatch's Deep Learning Summer School.
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Jul 18:
I am attending an ML conference for the first time:
ICML 2021.
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Jul 1:
I graduated from the BSc in Mathematical Engineering at Universidad
EAFIT! Plus, got a mention for my contributions to the student
organization. Check out my
Linkedin post.
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Jan 23:
I started Mandarin Chinese lessons at
Instituto Confucio.
我会说一点汉语.
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Jan 14:
I am auditing Ioannis Mitliagkas' graduate course on
Deep Learning Theory
at Université de Montréal.
2020 and beyond
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Jul 2020:
Jose Gallego-Posada,
PhD student at Mila will be my
supervisor for my undergraduate thesis. I will be working on deep
generative models.
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Jun 2019:
Now part of McKinsey & Co.
in Belgium as a research intern. Working with
Antoine Stevens and
Patrick Dehout
in ML for the agricultural and chemical industries.
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Jan 2019:
Arrived in Louvain-la-Neuve, Belgium for an exchange semestrer
at the Université Catholique de Louvain.
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Nov 2017:
I have been appointed as president of
CIGMA-OE, the
Mathematical Engineering chapter of the Student Organization at Universidad EAFIT.
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Dec 2015:
I was awarded a full scholarship for the Bachelor's degree in
Mathematical Engineering at Universidad EAFIT.
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Dec 2015:
Scored
amongst the best 0.1% on the Colombian high school examination ICFES.
Unfortunately, I did not obtain an Andrés Bello prize.
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Dec 2015:
Ranked first in the
National Chemistry Olympiads of Universidad de Antioquia.
Dec 17: Flexible Learning of Sparse Neural Networks via Constrained L0 Regularization, won the best poster award at the LatinX in AI Workshop @ NeurIPS 2021!
Nov 1: Starting an internship at Mila, a fundamental machine learning research lab. I will join Simon Lacoste-Julien's group under the supervision of Jose Gallego-Posada.
Oct 22: My first ever paper, Flexible Learning of Sparse Neural Networks via Constrained L0 Regularization, has been accepted at the LatinX in AI Workshop at NeurIPS 2021!
Aug 2: during the next three weeks, I will attend (virtually) Neuromatch's Deep Learning Summer School.
Jul 18: I am attending an ML conference for the first time: ICML 2021.
Jul 1: I graduated from the BSc in Mathematical Engineering at Universidad EAFIT! Plus, got a mention for my contributions to the student organization. Check out my Linkedin post.
Jan 23: I started Mandarin Chinese lessons at Instituto Confucio. 我会说一点汉语.
Jan 14: I am auditing Ioannis Mitliagkas' graduate course on Deep Learning Theory at Université de Montréal.
-
Jul 2020: Jose Gallego-Posada, PhD student at Mila will be my supervisor for my undergraduate thesis. I will be working on deep generative models.
-
Jun 2019: Now part of McKinsey & Co. in Belgium as a research intern. Working with Antoine Stevens and Patrick Dehout in ML for the agricultural and chemical industries.
-
Jan 2019: Arrived in Louvain-la-Neuve, Belgium for an exchange semestrer at the Université Catholique de Louvain.
-
Nov 2017: I have been appointed as president of CIGMA-OE, the Mathematical Engineering chapter of the Student Organization at Universidad EAFIT.
-
Dec 2015: I was awarded a full scholarship for the Bachelor's degree in Mathematical Engineering at Universidad EAFIT.
-
Dec 2015: Scored amongst the best 0.1% on the Colombian high school examination ICFES. Unfortunately, I did not obtain an Andrés Bello prize.
-
Dec 2015: Ranked first in the National Chemistry Olympiads of Universidad de Antioquia.
Publications
Conference
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Balancing Act: Constraining Disparate Impact in Sparse Models. M. Hashemizadeh*, J. Ramirez*, R. Sukumaran, G. Farnadi, S. Lacoste-Julien and J. Gallego-Posada. ICLR, 2024.
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Controlled Sparsity via Constrained Optimization or: How I Learned to Stop Tuning Penalties and Love Constraints. J. Gallego-Posada, J. Ramirez, A. Erraqabi, Y. Bengio and S. Lacoste-Julien. NeurIPS, 2022.
Workshop
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Omega: Optimistic EMA Gradients. J. Ramirez, R. Sukumaran, Q. Bertrand and G. Gidel. LatinX in AI workshop at ICML, 2023.
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L0onie: Compressing COINs with L0-constraints. J. Ramirez and J. Gallego-Posada. Sparsity in Neural Networks Workshop, 2022.
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Flexible Learning of Sparse Neural Networks via Constrained L0 Regularization. J. Gallego-Posada, J. Ramirez and A. Erraqabi. LatinX in AI Workshop at NeurIPS, 2021.
Libraries
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J. Gallego-Posada and J. Ramirez (2022). Cooper: a general-purpose library for constrained optimization in Pytorch [Computer software].
Teaching Assistantships
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Fall 23: Probabilistic Graphical Models by Simon Lacoste-Julien