Alessandro Achille

ORCID

Publication Activity (10 Years)

Years Active: 2016-2024
Publications (10 Years): 91

Top Venues

University of California, Los Angeles, USA (PHD)

Education History

University of California, Los Angeles, USA

PHD

Publications

Benjamin Biggs, Arjun Seshadri, Yang Zou, Achin Jain, Aditya Golatkar, Yusheng Xie, Alessandro Achille, Ashwin Swaminathan, Stefano Soatto
Diffusion Soup: Model Merging for Text-to-Image Diffusion Models. CoRR (2024)
Alessandro Achille, Greg Ver Steeg, Tian Yu Liu, Matthew Trager, Carson Klingenberg, Stefano Soatto
Interpretable Measures of Conceptual Similarity by Complexity-Constrained Descriptive Auto-Encoding. CoRR (2024)
Kaiwen Gui, Alexander M. Dalzell, Alessandro Achille, Martin Suchara, Frederic T. Chong
Spacetime-Efficient Low-Depth Quantum State Preparation with Applications. Quantum 8 (2024)
Michael Kleinman, Alessandro Achille, Stefano Soatto
Critical Learning Periods Emerge Even in Deep Linear Networks. ICLR (2024)
Alessandro Favero, Luca Zancato, Matthew Trager, Siddharth Choudhary, Pramuditha Perera, Alessandro Achille, Ashwin Swaminathan, Stefano Soatto
Multi-Modal Hallucination Control by Visual Information Grounding. CoRR (2024)
Matthew Trager, Alessandro Achille, Pramuditha Perera, Luca Zancato, Stefano Soatto
Compositional Structures in Neural Embedding and Interaction Decompositions. CoRR (2024)
Luca Zancato, Arjun Seshadri, Yonatan Dukler, Aditya Golatkar, Yantao Shen, Benjamin Bowman, Matthew Trager, Alessandro Achille, Stefano Soatto
B'MOJO: Hybrid State Space Realizations of Foundation Models with Eidetic and Fading Memory. CoRR (2024)
Tian Yu Liu, Matthew Trager, Alessandro Achille, Pramuditha Perera, Luca Zancato, Stefano Soatto
Meaning Representations from Trajectories in Autoregressive Models. ICLR (2024)
Aditya Golatkar, Alessandro Achille, Luca Zancato, Yu-Xiang Wang, Ashwin Swaminathan, Stefano Soatto
CPR: Retrieval Augmented Generation for Copyright Protection. CoRR (2024)
Xiang Xu, Tianchen Zhao, Zheng Zhang, Zhihua Li, Jon Wu, Alessandro Achille, Mani Srivastava
Principles of Designing Robust Remote Face Anti-Spoofing Systems. CoRR (2024)
Benet Oriol Sabat, Alessandro Achille, Matthew Trager, Stefano Soatto
NeRF-Insert: 3D Local Editing with Multimodal Control Signals. CoRR (2024)
Yonatan Dukler, Benjamin Bowman, Alessandro Achille, Aditya Golatkar, Ashwin Swaminathan, Stefano Soatto
SAFE: Machine Unlearning With Shard Graphs. ICCV (2023)
Alessandro Achille, Michael Kearns, Carson Klingenberg, Stefano Soatto
AI Model Disgorgement: Methods and Choices. CoRR (2023)
Achin Jain, Gurumurthy Swaminathan, Paolo Favaro, Hao Yang, Avinash Ravichandran, Hrayr Harutyunyan, Alessandro Achille, Onkar Dabeer, Bernt Schiele, Ashwin Swaminathan, Stefano Soatto
A Meta-Learning Approach to Predicting Performance and Data Requirements. CVPR (2023)
Yonatan Dukler, Alessandro Achille, Hao Yang, Varsha Vivek, Luca Zancato, Benjamin Bowman, Avinash Ravichandran, Charless C. Fowlkes, Ashwin Swaminathan, Stefano Soatto
Introspective Cross-Attention Probing for Lightweight Transfer of Pre-trained Models. CoRR (2023)
Marco Fumero, Florian Wenzel, Luca Zancato, Alessandro Achille, Emanuele Rodolà, Stefano Soatto, Bernhard Schölkopf, Francesco Locatello
Leveraging sparse and shared feature activations for disentangled representation learning. CoRR (2023)
Marco Fumero, Florian Wenzel, Luca Zancato, Alessandro Achille, Emanuele Rodolà, Stefano Soatto, Bernhard Schölkopf, Francesco Locatello
Leveraging sparse and shared feature activations for disentangled representation learning. NeurIPS (2023)
Benjamin Bowman, Alessandro Achille, Luca Zancato, Matthew Trager, Pramuditha Perera, Giovanni Paolini, Stefano Soatto
À-la-carte Prompt Tuning (APT): Combining Distinct Data Via Composable Prompting. CoRR (2023)
Chethan Parameshwara, Alessandro Achille, Matthew Trager, Xiaolong Li, Jiawei Mo, Matthew Trager, Ashwin Swaminathan, CJ Taylor, Dheera Venkatraman, Xiaohan Fei, Stefano Soatto
Towards Visual Foundational Models of Physical Scenes. CoRR (2023)
Yonatan Dukler, Benjamin Bowman, Alessandro Achille, Aditya Golatkar, Ashwin Swaminathan, Stefano Soatto
SAFE: Machine Unlearning With Shard Graphs. CoRR (2023)
Luca Zancato, Alessandro Achille, Tian Yu Liu, Matthew Trager, Pramuditha Perera, Stefano Soatto
Train/Test-Time Adaptation with Retrieval. CoRR (2023)
Matthew Trager, Pramuditha Perera, Luca Zancato, Alessandro Achille, Parminder Bhatia, Bing Xiang, Stefano Soatto
Linear Spaces of Meanings: the Compositional Language of VLMs. CoRR (2023)
Michael Kleinman, Alessandro Achille, Stefano Soatto
Critical Learning Periods for Multisensory Integration in Deep Networks. CVPR (2023)
Benjamin Bowman, Alessandro Achille, Luca Zancato, Matthew Trager, Pramuditha Perera, Giovanni Paolini, Stefano Soatto
À-la-carte Prompt Tuning (APT): Combining Distinct Data Via Composable Prompting. CVPR (2023)
Tian Yu Liu, Matthew Trager, Alessandro Achille, Pramuditha Perera, Luca Zancato, Stefano Soatto
Meaning Representations from Trajectories in Autoregressive Models. CoRR (2023)
Yonatan Dukler, Alessandro Achille, Hao Yang, Varsha Vivek, Luca Zancato, Benjamin Bowman, Avinash Ravichandran, Charless C. Fowlkes, Ashwin Swaminathan, Stefano Soatto
Your representations are in the network: composable and parallel adaptation for large scale models. NeurIPS (2023)
Michael Kleinman, Alessandro Achille, Stefano Soatto, Jonathan C. Kao
Gacs-Korner Common Information Variational Autoencoder. NeurIPS (2023)
Michael Kleinman, Alessandro Achille, Stefano Soatto
Critical Learning Periods Emerge Even in Deep Linear Networks. CoRR (2023)
Kaiwen Gui, Alexander M. Dalzell, Alessandro Achille, Martin Suchara, Frederic T. Chong
Spacetime-Efficient Low-Depth Quantum State Preparation with Applications. CoRR (2023)
Pramuditha Perera, Matthew Trager, Luca Zancato, Alessandro Achille, Stefano Soatto
Prompt Algebra for Task Composition. CoRR (2023)
Achin Jain, Gurumurthy Swaminathan, Paolo Favaro, Hao Yang, Avinash Ravichandran, Hrayr Harutyunyan, Alessandro Achille, Onkar Dabeer, Bernt Schiele, Ashwin Swaminathan, Stefano Soatto
A Meta-Learning Approach to Predicting Performance and Data Requirements. CoRR (2023)
Matthew Trager, Pramuditha Perera, Luca Zancato, Alessandro Achille, Parminder Bhatia, Stefano Soatto
Linear Spaces of Meanings: Compositional Structures in Vision-Language Models. ICCV (2023)
Aditya Golatkar, Alessandro Achille, Ashwin Swaminathan, Stefano Soatto
Training Data Protection with Compositional Diffusion Models. CoRR (2023)
Luca Zancato, Alessandro Achille, Tian Yu Liu, Matthew Trager, Pramuditha Perera, Stefano Soatto
Train/Test-Time Adaptation with Retrieval. CVPR (2023)
Aditya Golatkar, Alessandro Achille, Yu-Xiang Wang, Aaron Roth, Michael Kearns, Stefano Soatto
Mixed Differential Privacy in Computer Vision. CVPR (2022)
Matthew Wallingford, Hao Li, Alessandro Achille, Avinash Ravichandran, Charless C. Fowlkes, Rahul Bhotika, Stefano Soatto
Task Adaptive Parameter Sharing for Multi-Task Learning. CoRR (2022)
Mohamad Rida Rammal, Alessandro Achille, Aditya Golatkar, Suhas N. Diggavi, Stefano Soatto
On Leave-One-Out Conditional Mutual Information For Generalization. CoRR (2022)
Matthew Wallingford, Hao Li, Alessandro Achille, Avinash Ravichandran, Charless C. Fowlkes, Rahul Bhotika, Stefano Soatto
Task Adaptive Parameter Sharing for Multi-Task Learning. CVPR (2022)
Michael Kleinman, Alessandro Achille, Stefano Soatto
Critical Learning Periods for Multisensory Integration in Deep Networks. CoRR (2022)
Yonatan Dukler, Alessandro Achille, Giovanni Paolini, Avinash Ravichandran, Marzia Polito, Stefano Soatto
DIVA: Dataset Derivative of a Learning Task. ICLR (2022)
Simone Bombari, Alessandro Achille, Zijian Wang, Yu-Xiang Wang, Yusheng Xie, Kunwar Yashraj Singh, Srikar Appalaraju, Vijay Mahadevan, Stefano Soatto
Towards Differential Relational Privacy and its use in Question Answering. CoRR (2022)
Alessandro Achille, Stefano Soatto
On Binding Objects to Symbols: Learning Physical Concepts to Understand Real from Fake. CoRR (2022)
Mohamad Rida Rammal, Alessandro Achille, Aditya Golatkar, Suhas N. Diggavi, Stefano Soatto
On Leave-One-Out Conditional Mutual Information For Generalization. NeurIPS (2022)
Michael Kleinman, Alessandro Achille, Stefano Soatto, Jonathan C. Kao
Gacs-Korner Common Information Variational Autoencoder. CoRR (2022)
Tian Yu Liu, Aditya Golatkar, Stefano Soatto, Alessandro Achille
Integral Continual Learning Along the Tangent Vector Field of Tasks. CoRR (2022)
Aditya Golatkar, Alessandro Achille, Yu-Xiang Wang, Aaron Roth, Michael Kearns, Stefano Soatto
Mixed Differential Privacy in Computer Vision. CoRR (2022)
Aditya Deshpande, Alessandro Achille, Avinash Ravichandran, Hao Li, Luca Zancato, Charless C. Fowlkes, Rahul Bhotika, Stefano Soatto, Pietro Perona
A linearized framework and a new benchmark for model selection for fine-tuning. CoRR (2021)
Kamal Gupta, Justin Lazarow, Alessandro Achille, Larry Davis, Vijay Mahadevan, Abhinav Shrivastava
LayoutTransformer: Layout Generation and Completion with Self-attention. ICCV (2021)
Michael Kleinman, Alessandro Achille, Stefano Soatto, Jonathan C. Kao
Redundant Information Neural Estimation. Entropy 23 (7) (2021)
Hrayr Harutyunyan, Alessandro Achille, Giovanni Paolini, Orchid Majumder, Avinash Ravichandran, Rahul Bhotika, Stefano Soatto
Estimating informativeness of samples with Smooth Unique Information. ICLR (2021)
Hrayr Harutyunyan, Alessandro Achille, Giovanni Paolini, Orchid Majumder, Avinash Ravichandran, Rahul Bhotika, Stefano Soatto
Estimating informativeness of samples with Smooth Unique Information. CoRR (2021)
Giovanni Paolini, Ben Athiwaratkun, Jason Krone, Jie Ma, Alessandro Achille, Rishita Anubhai, Cícero Nogueira dos Santos, Bing Xiang, Stefano Soatto
Structured Prediction as Translation between Augmented Natural Languages. ICLR (2021)
Aditya Golatkar, Alessandro Achille, Avinash Ravichandran, Marzia Polito, Stefano Soatto
Mixed-Privacy Forgetting in Deep Networks. CVPR (2021)
Alessandro Achille, Aditya Golatkar, Avinash Ravichandran, Marzia Polito, Stefano Soatto
LQF: Linear Quadratic Fine-Tuning. CVPR (2021)
Matteo Terzi, Alessandro Achille, Marco Maggipinto, Gian Antonio Susto
Adversarial Training Reduces Information and Improves Transferability. AAAI (2021)
Julian G. Zilly, Alessandro Achille, Andrea Censi, Emilio Frazzoli
On Plasticity, Invariance, and Mutually Frozen Weights in Sequential Task Learning. NeurIPS (2021)
Michael Kleinman, Alessandro Achille, Daksh Idnani, Jonathan C. Kao
Usable Information and Evolution of Optimal Representations During Training. ICLR (2021)
Giovanni Paolini, Ben Athiwaratkun, Jason Krone, Jie Ma, Alessandro Achille, Rishita Anubhai, Cícero Nogueira dos Santos, Bing Xiang, Stefano Soatto
Structured Prediction as Translation between Augmented Natural Languages. CoRR (2021)
Yonatan Dukler, Alessandro Achille, Giovanni Paolini, Avinash Ravichandran, Marzia Polito, Stefano Soatto
DIVA: Dataset Derivative of a Learning Task. CoRR (2021)
Michael Kleinman, Daksh Idnani, Alessandro Achille, Jonathan C. Kao
Usable Information and Evolution of Optimal Representations During Training. CoRR (2020)
Aditya Golatkar, Alessandro Achille, Avinash Ravichandran, Marzia Polito, Stefano Soatto
Mixed-Privacy Forgetting in Deep Networks. CoRR (2020)
Luca Zancato, Alessandro Achille, Avinash Ravichandran, Rahul Bhotika, Stefano Soatto
Predicting Training Time Without Training. CoRR (2020)
Aditya Golatkar, Alessandro Achille, Stefano Soatto
Forgetting Outside the Box: Scrubbing Deep Networks of Information Accessible from Input-Output Observations. ECCV (29) (2020)
Matteo Terzi, Alessandro Achille, Marco Maggipinto, Gian Antonio Susto
Adversarial Training Reduces Information and Improves Transferability. CoRR (2020)
Kamal Gupta, Alessandro Achille, Justin Lazarow, Larry Davis, Vijay Mahadevan, Abhinav Shrivastava
Layout Generation and Completion with Self-attention. CoRR (2020)
Luca Zancato, Alessandro Achille, Avinash Ravichandran, Rahul Bhotika, Stefano Soatto
Predicting Training Time Without Training. NeurIPS (2020)
Aditya Golatkar, Alessandro Achille, Stefano Soatto
Forgetting Outside the Box: Scrubbing Deep Networks of Information Accessible from Input-Output Observations. CoRR (2020)
Aditya Golatkar, Alessandro Achille, Stefano Soatto
Eternal Sunshine of the Spotless Net: Selective Forgetting in Deep Networks. CVPR (2020)
Qing Liu, Orchid Majumder, Alessandro Achille, Avinash Ravichandran, Rahul Bhotika, Stefano Soatto
Incremental Few-Shot Meta-learning via Indirect Discriminant Alignment. ECCV (7) (2020)
Alessandro Achille, Aditya Golatkar, Avinash Ravichandran, Marzia Polito, Stefano Soatto
LQF: Linear Quadratic Fine-Tuning. CoRR (2020)
Alessandro Achille, Giovanni Paolini, Glen Mbeng, Stefano Soatto
The Information Complexity of Learning Tasks, their Structure and their Distance. CoRR (2019)
Alessandro Achille, Matteo Rovere, Stefano Soatto
Critical Learning Periods in Deep Networks. ICLR (Poster) (2019)
Alessandro Achille, Michael Lam, Rahul Tewari, Avinash Ravichandran, Subhransu Maji, Charless C. Fowlkes, Stefano Soatto, Pietro Perona
Task2Vec: Task Embedding for Meta-Learning. CoRR (2019)
Joël Seytre, Jon Wu, Alessandro Achille
TextTubes for Detecting Curved Text in the Wild. CoRR (2019)
Cuong V. Nguyen, Alessandro Achille, Michael Lam, Tal Hassner, Vijay Mahadevan, Stefano Soatto
Toward Understanding Catastrophic Forgetting in Continual Learning. CoRR (2019)
Aditya Golatkar, Alessandro Achille, Stefano Soatto
Eternal Sunshine of the Spotless Net: Selective Forgetting in Deep Networks. CoRR (2019)
Aditya Golatkar, Alessandro Achille, Stefano Soatto
Time Matters in Regularizing Deep Networks: Weight Decay and Data Augmentation Affect Early Learning Dynamics, Matter Little Near Convergence. CoRR (2019)
Aditya Golatkar, Alessandro Achille, Stefano Soatto
Time Matters in Regularizing Deep Networks: Weight Decay and Data Augmentation Affect Early Learning Dynamics, Matter Little Near Convergence. NeurIPS (2019)
Alessandro Achille, Stefano Soatto
Where is the Information in a Deep Neural Network? CoRR (2019)
Alessandro Achille, Michael Lam, Rahul Tewari, Avinash Ravichandran, Subhransu Maji, Charless C. Fowlkes, Stefano Soatto, Pietro Perona
Task2Vec: Task Embedding for Meta-Learning. ICCV (2019)
Alessandro Achille, Glen Mbeng, Stefano Soatto
The Dynamics of Differential Learning I: Information-Dynamics and Task Reachability. CoRR (2018)
Alessandro Achille, Stefano Soatto
A Separation Principle for Control in the Age of Deep Learning. Annu. Rev. Control. Robotics Auton. Syst. 1 (2018)
Alessandro Achille, Stefano Soatto
Emergence of Invariance and Disentanglement in Deep Representations. J. Mach. Learn. Res. 19 (2018)
Alessandro Achille, Stefano Soatto
Emergence of Invariance and Disentanglement in Deep Representations. ITA (2018)
Alessandro Achille, Tom Eccles, Loïc Matthey, Christopher Burgess, Nicholas Watters, Alexander Lerchner, Irina Higgins
Life-Long Disentangled Representation Learning with Cross-Domain Latent Homologies. NeurIPS (2018)
Alessandro Achille, Stefano Soatto
Information Dropout: Learning Optimal Representations Through Noisy Computation. IEEE Trans. Pattern Anal. Mach. Intell. 40 (12) (2018)
Alessandro Achille, Tom Eccles, Loïc Matthey, Christopher P. Burgess, Nick Watters, Alexander Lerchner, Irina Higgins
Life-Long Disentangled Representation Learning with Cross-Domain Latent Homologies. CoRR (2018)
Alessandro Achille, Stefano Soatto
On the Emergence of Invariance and Disentangling in Deep Representations. CoRR (2017)
Alessandro Achille, Stefano Soatto
A Separation Principle for Control in the Age of Deep Learning. CoRR (2017)
Alessandro Achille, Matteo Rovere, Stefano Soatto
Critical Learning Periods in Deep Neural Networks. CoRR (2017)
Alessandro Achille, Stefano Soatto
Information Dropout: learning optimal representations through noise. CoRR (2016)

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Publication Activity (10 Years)

Top Topics

Top Venues

Alessandro Achille