Bernacchia, Alberto

22 publications

ICML 2025 Bayesian Optimization from Human Feedback: Near-Optimal Regret Bounds Aya Kayal, Sattar Vakili, Laura Toni, Da-Shan Shiu, Alberto Bernacchia

ICML 2025 Global Curvature for Second-Order Optimization of Neural Networks Alberto Bernacchia

AISTATS 2025 Near-Optimal Sample Complexity in Reward-Free Kernel-Based Reinforcement Learning Aya Kayal, Sattar Vakili, Laura Toni, Alberto Bernacchia

NeurIPSW 2024 Comparing Implicit and Denoising Score-Matching Objectives Artem Artemev, Ayan Das, Farhang Nabiei, Alberto Bernacchia

NeurIPSW 2024 Efficient Model Compression Techniques with FishLeg Jamie McGowan, Wei Sheng Lai, Weibin Chen, Henry Aldridge, Jools Clarke, Jezabel R Garcia, Rui Xia, Yilei Liang, Guillaume Hennequin, Alberto Bernacchia

NeurIPS 2024 Exact, Tractable Gauss-Newton Optimization in Deep Reversible Architectures Reveal Poor Generalization Davide Buffelli, Jamie McGowan, Wangkun Xu, Alexandru Cioba, Da-shan Shiu, Guillaume Hennequin, Alberto Bernacchia

ICML 2024 Reward-Free Kernel-Based Reinforcement Learning Sattar Vakili, Farhang Nabiei, Da-Shan Shiu, Alberto Bernacchia

NeurIPSW 2024 Stutter Makes Smarter: Learning Self-Improvement for Large Language Models Pei-Chen Ho, Meng-Hsi Chen, Alberto Bernacchia, Philipp Ennen, Yen-Chen Wu, Da-shan Shiu

ICML 2023 Delayed Feedback in Kernel Bandits Sattar Vakili, Danyal Ahmed, Alberto Bernacchia, Ciara Pike-Burke

ICLR 2023 Fisher-Legendre (FishLeg) Optimization of Deep Neural Networks Jezabel R Garcia, Federica Freddi, Stathi Fotiadis, Maolin Li, Sattar Vakili, Alberto Bernacchia, Guillaume Hennequin

ICML 2023 Image Generation with Shortest Path Diffusion Ayan Das, Stathi Fotiadis, Anil Batra, Farhang Nabiei, Fengting Liao, Sattar Vakili, Da-Shan Shiu, Alberto Bernacchia

AISTATS 2023 Sample Complexity of Kernel-Based Q-Learning Sing-Yuan Yeh, Fu-Chieh Chang, Chang-Wei Yueh, Pei-Yuan Wu, Alberto Bernacchia, Sattar Vakili

NeurIPSW 2022 Gradient Descent: Robustness to Adversarial Corruption Fu-Chieh Chang, Farhang Nabiei, Pei-Yuan Wu, Alexandru Cioba, Sattar Vakili, Alberto Bernacchia

AAAI 2022 How to Distribute Data Across Tasks for Meta-Learning? Alexandru Cioba, Michael Bromberg, Qian Wang, Ritwik Niyogi, Georgios Batzolis, Jezabel R. Garcia, Da-Shan Shiu, Alberto Bernacchia

ICML 2022 Improved Convergence Rates for Sparse Approximation Methods in Kernel-Based Learning Sattar Vakili, Jonathan Scarlett, Da-Shan Shiu, Alberto Bernacchia

NeurIPSW 2021 Cyclic Orthogonal Convolutions for Long-Range Integration of Features Federica Freddi, Jezabel R Garcia, Michael Bromberg, Sepehr Jalali, Da-shan Shiu, Alvin Chua, Alberto Bernacchia

NeurIPSW 2021 How to Distribute Data Across Tasks for Meta-Learning? Alexandru Cioba, Michael Bromberg, Qian Wang, Ritwik Niyogi, Georgios Batzolis, Jezabel R Garcia, Da-shan Shiu, Alberto Bernacchia

ICLR 2021 Meta-Learning with Negative Learning Rates Alberto Bernacchia

NeurIPS 2021 Natural Continual Learning: Success Is a Journey, Not (just) a Destination Ta-Chu Kao, Kristopher Jensen, Gido van de Ven, Alberto Bernacchia, Guillaume Hennequin

NeurIPS 2021 Optimal Order Simple Regret for Gaussian Process Bandits Sattar Vakili, Nacime Bouziani, Sepehr Jalali, Alberto Bernacchia, Da-shan Shiu

NeurIPS 2020 Non-Reversible Gaussian Processes for Identifying Latent Dynamical Structure in Neural Data Virginia Rutten, Alberto Bernacchia, Maneesh Sahani, Guillaume Hennequin

NeurIPS 2018 Exact Natural Gradient in Deep Linear Networks and Its Application to the Nonlinear Case Alberto Bernacchia, Mate Lengyel, Guillaume Hennequin