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ORCIDJohan S. Obando-Ceron
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Journal Articles
- 2024
[j2]Johan Samir Obando-Ceron, João Guilherme Madeira Araújo, Aaron C. Courville, Pablo Samuel Castro:
On the consistency of hyper-parameter selection in value-based deep reinforcement learning. RLJ 3: 1037-1059 (2024)- [j1]Timon Willi, Johan Samir Obando-Ceron, Jakob Nicolaus Foerster, Gintare Karolina Dziugaite, Pablo Samuel Castro:
Mixture of Experts in a Mixture of RL settings. RLJ 3: 1072-1105 (2024)
Conference and Workshop Papers
- 2024
- [c6]Johan Samir Obando-Ceron, Aaron C. Courville, Pablo Samuel Castro:
In value-based deep reinforcement learning, a pruned network is a good network. ICML 2024 - [c5]Johan Samir Obando-Ceron, Ghada Sokar, Timon Willi, Clare Lyle, Jesse Farebrother, Jakob Nicolaus Foerster, Gintare Karolina Dziugaite, Doina Precup, Pablo Samuel Castro:
Mixtures of Experts Unlock Parameter Scaling for Deep RL. ICML 2024 - 2023
- [c4]Johan Samir Obando-Ceron, Marc G. Bellemare, Pablo Samuel Castro:
The Small Batch Size Anomaly in Multistep Deep Reinforcement Learning. Tiny Papers @ ICLR 2023 - [c3]Max Schwarzer, Johan Samir Obando-Ceron, Aaron C. Courville, Marc G. Bellemare, Rishabh Agarwal, Pablo Samuel Castro:
Bigger, Better, Faster: Human-level Atari with human-level efficiency. ICML 2023: 30365-30380 - [c2]Johan S. Obando-Ceron, Marc G. Bellemare, Pablo Samuel Castro:
Small batch deep reinforcement learning. NeurIPS 2023 - 2021
- [c1]Johan Samir Obando-Ceron, Pablo Samuel Castro:
Revisiting Rainbow: Promoting more insightful and inclusive deep reinforcement learning research. ICML 2021: 1373-1383
Informal and Other Publications
- 2024
- [i14]Johan S. Obando-Ceron, Ghada Sokar, Timon Willi, Clare Lyle, Jesse Farebrother, Jakob N. Foerster, Gintare Karolina Dziugaite, Doina Precup, Pablo Samuel Castro:
Mixtures of Experts Unlock Parameter Scaling for Deep RL. CoRR abs/2402.08609 (2024) - [i13]Johan S. Obando-Ceron, Aaron C. Courville, Pablo Samuel Castro:
In deep reinforcement learning, a pruned network is a good network. CoRR abs/2402.12479 (2024) - [i12]Johan S. Obando-Ceron, João G. M. Araújo, Aaron C. Courville, Pablo Samuel Castro:
On the consistency of hyper-parameter selection in value-based deep reinforcement learning. CoRR abs/2406.17523 (2024) - [i11]Timon Willi, Johan S. Obando-Ceron, Jakob N. Foerster, Karolina Dziugaite, Pablo Samuel Castro:
Mixture of Experts in a Mixture of RL settings. CoRR abs/2406.18420 (2024) - [i10]Ghada Sokar, Johan S. Obando-Ceron, Aaron C. Courville, Hugo Larochelle, Pablo Samuel Castro:
Don't flatten, tokenize! Unlocking the key to SoftMoE's efficacy in deep RL. CoRR abs/2410.01930 (2024) - [i9]Jiashun Liu, Johan S. Obando-Ceron, Aaron C. Courville, Ling Pan:
Neuroplastic Expansion in Deep Reinforcement Learning. CoRR abs/2410.07994 (2024) - [i8]Ashmal Vayani, Dinura Dissanayake, Hasindri Watawana, Noor Ahsan, Nevasini Sasikumar, Omkar Thawakar, Henok Biadglign Ademtew, Yahya Hmaiti, Amandeep Kumar, Kartik Kuckreja, Mykola Maslych, Wafa Al Ghallabi, Mihail Mihaylov, Chao Qin, Abdelrahman M. Shaker, Mike Zhang, Mahardika Krisna Ihsani, Amiel Esplana, Monil Gokani, Shachar Mirkin, Harsh Singh, Ashay Srivastava, Endre Hamerlik, Fathinah Asma Izzati, Fadillah Adamsyah Maani, Sebastian Cavada, Jenny Chim, Rohit Gupta, Sanjay Manjunath, Kamila Zhumakhanova, Feno Heriniaina Rabevohitra, Azril Amirudin, Muhammad Ridzuan, Daniya Kareem, Ketan More, Kunyang Li, Pramesh Shakya, Muhammad Saad, Amirpouya Ghasemaghaei, Amirbek Djanibekov, Dilshod Azizov, Branislava Jankovic, Naman Bhatia, Alvaro Cabrera, Johan S. Obando-Ceron, Olympiah Otieno, Fabian Farestam, Muztoba Rabbani, Sanoojan Baliah, Santosh Sanjeev, Abduragim Shtanchaev, Maheen Fatima, Thao Nguyen, Amrin Kareem, Toluwani Aremu, Nathan Xavier, Amit Bhatkal, Hawau Toyin, Aman Chadha, Hisham Cholakkal, Rao Muhammad Anwer, Michael Felsberg, Jorma Laaksonen, Thamar Solorio, Monojit Choudhury, Ivan Laptev, Mubarak Shah, Salman Khan, Fahad Khan:
All Languages Matter: Evaluating LMMs on Culturally Diverse 100 Languages. CoRR abs/2411.16508 (2024) - 2023
- [i7]Joo Hyung Lee, Wonpyo Park, Nicole Mitchell, Jonathan Pilault, Johan S. Obando-Ceron, Han-Byul Kim, Namhoon Lee, Elias Frantar, Yun Long, Amir Yazdanbakhsh, Shivani Agrawal, Suvinay Subramanian, Xin Wang, Sheng-Chun Kao, Xingyao Zhang, Trevor Gale, Aart Bik, Woohyun Han, Milen Ferev, Zhonglin Han, Hong-Seok Kim, Yann N. Dauphin, Karolina Dziugaite, Pablo Samuel Castro, Utku Evci:
JaxPruner: A concise library for sparsity research. CoRR abs/2304.14082 (2023) - [i6]Max Schwarzer, Johan S. Obando-Ceron, Aaron C. Courville, Marc G. Bellemare, Rishabh Agarwal, Pablo Samuel Castro:
Bigger, Better, Faster: Human-level Atari with human-level efficiency. CoRR abs/2305.19452 (2023) - [i5]Johan S. Obando-Ceron, Victor Romero-Cano, Sildomar Monteiro:
Probabilistic Multimodal Depth Estimation Based on Camera-LiDAR Sensor Fusion. CoRR abs/2307.10519 (2023) - [i4]Johan S. Obando-Ceron, Marc G. Bellemare, Pablo Samuel Castro:
Small batch deep reinforcement learning. CoRR abs/2310.03882 (2023) - 2020
- [i3]Johan S. Obando-Ceron, Pablo Samuel Castro:
Revisiting Rainbow: Promoting more insightful and inclusive deep reinforcement learning research. CoRR abs/2011.14826 (2020) - 2019
- [i2]Johan S. Obando-Ceron, Victor Romero-Cano, Walter Mayor Toro:
Exploiting the potential of deep reinforcement learning for classification tasks in high-dimensional and unstructured data. CoRR abs/1912.09595 (2019) - [i1]Walter M. Mayor Toro, Juan Carlos Perafan Villota, Oscar H. Mondragon, Johan S. Obando-Ceron:
Divide and Conquer: an Accurate Machine Learning Algorithm to Process Split Videos on a Parallel Processing Infrastructure. CoRR abs/1912.09601 (2019)
Coauthor Index
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