Hanie Sedghi

Publication Activity (10 Years)

Years Active: 2010-2024
Publications (10 Years): 40

Top Topics

Generalization Bounds

Tensor Factorization

Top Venues

ICLR (Workshop)

Publications

Bernd Bohnet, Kevin Swersky, Rosanne Liu, Pranjal Awasthi, Azade Nova, Javier Snaider, Hanie Sedghi, Aaron T. Parisi, Michael Collins, Angeliki Lazaridou, Orhan Firat, Noah Fiedel
Long-Span Question-Answering: Automatic Question Generation and QA-System Ranking via Side-by-Side Evaluation. CoRR (2024)
Bernd Bohnet, Azade Nova, Aaron T. Parisi, Kevin Swersky, Katayoon Goshvadi, Hanjun Dai, Dale Schuurmans, Noah Fiedel, Hanie Sedghi
Exploring and Benchmarking the Planning Capabilities of Large Language Models. CoRR (2024)
Avi Singh, John D. Co-Reyes, Rishabh Agarwal, Ankesh Anand, Piyush Patil, Xavier Garcia, Peter J. Liu, James Harrison, Jaehoon Lee, Kelvin Xu, Aaron T. Parisi, Abhishek Kumar, Alexander A. Alemi, Alex Rizkowsky, Azade Nova, Ben Adlam, Bernd Bohnet, Gamaleldin Fathy Elsayed, Hanie Sedghi, Igor Mordatch, Isabelle Simpson, Izzeddin Gur, Jasper Snoek, Jeffrey Pennington, Jiri Hron, Kathleen Kenealy, Kevin Swersky, Kshiteej Mahajan, Laura Culp, Lechao Xiao, Maxwell L. Bileschi, Noah Constant, Roman Novak, Rosanne Liu, Tris Warkentin, Yundi Qian, Yamini Bansal, Ethan Dyer, Behnam Neyshabur, Jascha Sohl-Dickstein, Noah Fiedel
Beyond Human Data: Scaling Self-Training for Problem-Solving with Language Models. Trans. Mach. Learn. Res. 2024 (2024)
Avi Singh, John D. Co-Reyes, Rishabh Agarwal, Ankesh Anand, Piyush Patil, Xavier Garcia, Peter J. Liu, James Harrison, Jaehoon Lee, Kelvin Xu, Aaron Parisi, Abhishek Kumar, Alex Alemi, Alex Rizkowsky, Azade Nova, Ben Adlam, Bernd Bohnet, Gamaleldin F. Elsayed, Hanie Sedghi, Igor Mordatch, Isabelle Simpson, Izzeddin Gur, Jasper Snoek, Jeffrey Pennington, Jiri Hron, Kathleen Kenealy, Kevin Swersky, Kshiteej Mahajan, Laura Culp, Lechao Xiao, Maxwell L. Bileschi, Noah Constant, Roman Novak, Rosanne Liu, Tris Warkentin, Yundi Qian, Yamini Bansal, Ethan Dyer, Behnam Neyshabur, Jascha Sohl-Dickstein, Noah Fiedel
Beyond Human Data: Scaling Self-Training for Problem-Solving with Language Models. CoRR (2023)
Mahsa Forouzesh, Hanie Sedghi, Patrick Thiran
Leveraging Unlabeled Data to Track Memorization. ICLR (2023)
Pratyush Maini, Michael Curtis Mozer, Hanie Sedghi, Zachary Chase Lipton, J. Zico Kolter, Chiyuan Zhang
Can Neural Network Memorization Be Localized? ICML (2023)
Rahim Entezari, Mitchell Wortsman, Olga Saukh, Moein Shariatnia, Hanie Sedghi, Ludwig Schmidt
The Role of Pre-training Data in Transfer Learning. CoRR (2023)
Keller Jordan, Hanie Sedghi, Olga Saukh, Rahim Entezari, Behnam Neyshabur
REPAIR: REnormalizing Permuted Activations for Interpolation Repair. ICLR (2023)
Pratyush Maini, Michael C. Mozer, Hanie Sedghi, Zachary C. Lipton, J. Zico Kolter, Chiyuan Zhang
Can Neural Network Memorization Be Localized? CoRR (2023)
C. Daniel Freeman, Laura Culp, Aaron Parisi, Maxwell L. Bileschi, Gamaleldin F. Elsayed, Alex Rizkowsky, Isabelle Simpson, Alex Alemi, Azade Nova, Ben Adlam, Bernd Bohnet, Gaurav Mishra, Hanie Sedghi, Igor Mordatch, Izzeddin Gur, Jaehoon Lee, John D. Co-Reyes, Jeffrey Pennington, Kelvin Xu, Kevin Swersky, Kshiteej Mahajan, Lechao Xiao, Rosanne Liu, Simon Kornblith, Noah Constant, Peter J. Liu, Roman Novak, Yundi Qian, Noah Fiedel, Jascha Sohl-Dickstein
Frontier Language Models are not Robust to Adversarial Arithmetic, or "What do I need to say so you agree 2+2=5? CoRR (2023)
Saurabh Garg, Sivaraman Balakrishnan, Zachary Chase Lipton, Behnam Neyshabur, Hanie Sedghi
Leveraging unlabeled data to predict out-of-distribution performance. ICLR (2022)
Hattie Zhou, Azade Nova, Hugo Larochelle, Aaron C. Courville, Behnam Neyshabur, Hanie Sedghi
Teaching Algorithmic Reasoning via In-context Learning. CoRR (2022)
Lukas Timpl, Rahim Entezari, Hanie Sedghi, Behnam Neyshabur, Olga Saukh
Understanding the effect of sparsity on neural networks robustness. CoRR (2022)
Mahsa Forouzesh, Hanie Sedghi, Patrick Thiran
Leveraging Unlabeled Data to Track Memorization. CoRR (2022)
Amr Khalifa, Michael C. Mozer, Hanie Sedghi, Behnam Neyshabur, Ibrahim Alabdulmohsin
Layer-Stack Temperature Scaling. CoRR (2022)
Samira Abnar, Mostafa Dehghani, Behnam Neyshabur, Hanie Sedghi
Exploring the Limits of Large Scale Pre-training. ICLR (2022)
Keller Jordan, Hanie Sedghi, Olga Saukh, Rahim Entezari, Behnam Neyshabur
REPAIR: REnormalizing Permuted Activations for Interpolation Repair. CoRR (2022)
Rahim Entezari, Hanie Sedghi, Olga Saukh, Behnam Neyshabur
The Role of Permutation Invariance in Linear Mode Connectivity of Neural Networks. ICLR (2022)
Saurabh Garg, Sivaraman Balakrishnan, Zachary C. Lipton, Behnam Neyshabur, Hanie Sedghi
Leveraging Unlabeled Data to Predict Out-of-Distribution Performance. CoRR (2022)
Preetum Nakkiran, Behnam Neyshabur, Hanie Sedghi
The Deep Bootstrap Framework: Good Online Learners are Good Offline Generalizers. ICLR (2021)
Samira Abnar, Mostafa Dehghani, Behnam Neyshabur, Hanie Sedghi
Exploring the Limits of Large Scale Pre-training. CoRR (2021)
Rahim Entezari, Hanie Sedghi, Olga Saukh, Behnam Neyshabur
The Role of Permutation Invariance in Linear Mode Connectivity of Neural Networks. CoRR (2021)
Samira Abnar, Rianne van den Berg, Golnaz Ghiasi, Mostafa Dehghani, Nal Kalchbrenner, Hanie Sedghi
Gradual Domain Adaptation in the Wild: When Intermediate Distributions are Absent. CoRR (2021)
Niladri S. Chatterji, Behnam Neyshabur, Hanie Sedghi
The intriguing role of module criticality in the generalization of deep networks. ICLR (2020)
Behnam Neyshabur, Hanie Sedghi, Chiyuan Zhang
What is being transferred in transfer learning? CoRR (2020)
Behnam Neyshabur, Hanie Sedghi, Chiyuan Zhang
What is being transferred in transfer learning? NeurIPS (2020)
Philip M. Long, Hanie Sedghi
Generalization bounds for deep convolutional neural networks. ICLR (2020)
Preetum Nakkiran, Behnam Neyshabur, Hanie Sedghi
The Deep Bootstrap: Good Online Learners are Good Offline Generalizers. CoRR (2020)
Philip M. Long, Hanie Sedghi
On the effect of the activation function on the distribution of hidden nodes in a deep network. CoRR (2019)
Philip M. Long, Hanie Sedghi
Size-free generalization bounds for convolutional neural networks. CoRR (2019)
Niladri S. Chatterji, Behnam Neyshabur, Hanie Sedghi
The intriguing role of module criticality in the generalization of deep networks. CoRR (2019)
Hanie Sedghi, Vineet Gupta, Philip M. Long
The Singular Values of Convolutional Layers. ICLR (Poster) (2019)
Alexander Ratner, Dan Alistarh, Gustavo Alonso, David G. Andersen, Peter Bailis, Sarah Bird, Nicholas Carlini, Bryan Catanzaro, Eric Chung, Bill Dally, Jeff Dean, Inderjit S. Dhillon, Alexandros G. Dimakis, Pradeep Dubey, Charles Elkan, Grigori Fursin, Gregory R. Ganger, Lise Getoor, Phillip B. Gibbons, Garth A. Gibson, Joseph E. Gonzalez, Justin Gottschlich, Song Han, Kim M. Hazelwood, Furong Huang, Martin Jaggi, Kevin G. Jamieson, Michael I. Jordan, Gauri Joshi, Rania Khalaf, Jason Knight, Jakub Konecný, Tim Kraska, Arun Kumar, Anastasios Kyrillidis, Jing Li, Samuel Madden, H. Brendan McMahan, Erik Meijer, Ioannis Mitliagkas, Rajat Monga, Derek Gordon Murray, Dimitris S. Papailiopoulos, Gennady Pekhimenko, Theodoros Rekatsinas, Afshin Rostamizadeh, Christopher Ré, Christopher De Sa, Hanie Sedghi, Siddhartha Sen, Virginia Smith, Alex Smola, Dawn Song, Evan R. Sparks, Ion Stoica, Vivienne Sze, Madeleine Udell, Joaquin Vanschoren, Shivaram Venkataraman, Rashmi Vinayak, Markus Weimer, Andrew Gordon Wilson, Eric P. Xing, Matei Zaharia, Ce Zhang, Ameet Talwalkar
SysML: The New Frontier of Machine Learning Systems. CoRR (2019)
Philip M. Long, Hanie Sedghi
On the Effect of the Activation Function on the Distribution of Hidden Nodes in a Deep Network. Neural Comput. 31 (12) (2019)
Hanie Sedghi, Ashish Sabharwal
Knowledge Completion for Generics Using Guided Tensor Factorization. Trans. Assoc. Comput. Linguistics 6 (2018)
Hanie Sedghi, Vineet Gupta, Philip M. Long
The Singular Values of Convolutional Layers. CoRR (2018)
Ashish Sabharwal, Hanie Sedghi
How Good Are My Predictions? Efficiently Approximating Precision-Recall Curves for Massive Datasets. UAI (2017)
Hanie Sedghi, Anima Anandkumar
Training Input-Output Recurrent Neural Networks through Spectral Methods. CoRR (2016)
Hanie Sedghi, Majid Janzamin, Anima Anandkumar
Provable Tensor Methods for Learning Mixtures of Generalized Linear Models. AISTATS (2016)
Hanie Sedghi, Ashish Sabharwal
Knowledge Completion for Generics using Guided Tensor Factorization. CoRR (2016)
Majid Janzamin, Hanie Sedghi, Anima Anandkumar
Score Function Features for Discriminative Learning. ICLR (Workshop) (2015)
Hanie Sedghi, Edmond A. Jonckheere
Statistical Structure Learning to Ensure Data Integrity in Smart Grid. IEEE Trans. Smart Grid 6 (4) (2015)
Majid Janzamin, Hanie Sedghi, Anima Anandkumar
Generalization Bounds for Neural Networks through Tensor Factorization. CoRR (2015)
Anima Anandkumar, Hanie Sedghi
Learning Mixed Membership Community Models in Social Tagging Networks through Tensor Methods. CoRR (2015)
Hanie Sedghi, Anima Anandkumar
Provable Methods for Training Neural Networks with Sparse Connectivity. ICLR (Workshop) (2015)
Majid Janzamin, Hanie Sedghi, U. N. Niranjan, Animashree Anandkumar
FEAST at Play: Feature ExtrAction using Score function Tensors. FE@NIPS (2015)
Hanie Sedghi, Anima Anandkumar, Edmond A. Jonckheere
Multi-Step Stochastic ADMM in High Dimensions: Applications to Sparse Optimization and Matrix Decomposition. NIPS (2014)
Hanie Sedghi, Anima Anandkumar
Provable Tensor Methods for Learning Mixtures of Classifiers. CoRR (2014)
Hanie Sedghi, Edmond A. Jonckheere
Statistical Structure Learning, Towards a Robust Smart Grid. CoRR (2014)
Majid Janzamin, Hanie Sedghi, Anima Anandkumar
Score Function Features for Discriminative Learning: Matrix and Tensor Framework. CoRR (2014)
Hanie Sedghi, Anima Anandkumar, Edmond A. Jonckheere
Guarantees for Multi-Step Stochastic ADMM in High Dimensions. CoRR (2014)
Majid Janzamin, Mohammad Reza Pakravan, Hanie Sedghi
A Game-Theoretic Approach for Power Allocation in Bidirectional Cooperative Communication. WCNC (2010)