Hanie Sedghi - RankMe

57 papers A* 11A 2B 1Journal 37Unranked 5

Year	Rank	Type	Title / Venue / Authors
2025	J	`jnl`	Enhancing LLM Planning Capabilities through Intrinsic Self-Critique. CoRR Bernd Bohnet, Pierre-Alexandre Kamienny, Hanie Sedghi, Dilan Görür, Pranjal Awasthi, Aaron Parisi, Kevin Swersky, Rosanne Liu, Azade Nova, Noah Fiedel
2025	A*	`conf`	Improving Large Language Model Planning with Action Sequence Similarity. ICLR Xinran Zhao, Hanie Sedghi, Bernd Bohnet, Dale Schuurmans, Azade Nova
2025	J	`jnl`	Improving Large Language Model Planning with Action Sequence Similarity. CoRR Xinran Zhao, Hanie Sedghi, Bernd Bohnet, Dale Schuurmans, Azade Nova
2024	J	`jnl`	Beyond Human Data: Scaling Self-Training for Problem-Solving with Language Models. Trans. Mach. Learn. Res. 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
2024	J	`jnl`	Exploring and Benchmarking the Planning Capabilities of Large Language Models. CoRR Bernd Bohnet, Azade Nova, Aaron T. Parisi, Kevin Swersky, Katayoon Goshvadi, Hanjun Dai, Dale Schuurmans, Noah Fiedel, Hanie Sedghi
2024	J	`jnl`	Long-Span Question-Answering: Automatic Question Generation and QA-System Ranking via Side-by-Side Evaluation. CoRR 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
2024	J	`jnl`	Training Language Models on the Knowledge Graph: Insights on Hallucinations and Their Detectability. CoRR Jiri Hron, Laura Culp, Gamaleldin F. Elsayed, Rosanne Liu, Ben Adlam, Maxwell L. Bileschi, Bernd Bohnet, JD Co-Reyes, Noah Fiedel, C. Daniel Freeman, Izzeddin Gur, Kathleen Kenealy, Jaehoon Lee, Peter J. Liu, Gaurav Mishra, Igor Mordatch, Azade Nova, Roman Novak, Aaron Parisi, Jeffrey Pennington, Alex Rizkowsky, Isabelle Simpson, Hanie Sedghi, Jascha Sohl-Dickstein, Kevin Swersky, Sharad Vikram, Tris Warkentin, Lechao Xiao, Kelvin Xu, Jasper Snoek, Simon Kornblith
2023	J	`jnl`	Beyond Human Data: Scaling Self-Training for Problem-Solving with Language Models. CoRR 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
2023	A*	`conf`	Can Neural Network Memorization Be Localized? ICML Pratyush Maini, Michael Curtis Mozer, Hanie Sedghi, Zachary Chase Lipton, J. Zico Kolter, Chiyuan Zhang
2023	J	`jnl`	Can Neural Network Memorization Be Localized? CoRR Pratyush Maini, Michael C. Mozer, Hanie Sedghi, Zachary C. Lipton, J. Zico Kolter, Chiyuan Zhang
2023	—	`ed.`	Conference on Lifelong Learning Agents, 22-25 August 2023, McGill University, Montréal, Québec, Canada. CoLLAs Sarath Chandar, Razvan Pascanu, Hanie Sedghi, Doina Precup
2023	J	`jnl`	Frontier Language Models are not Robust to Adversarial Arithmetic, or "What do I need to say so you agree 2+2=5? CoRR 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
2023	A*	`conf`	Leveraging Unlabeled Data to Track Memorization. ICLR Mahsa Forouzesh, Hanie Sedghi, Patrick Thiran
2023	A*	`conf`	REPAIR: REnormalizing Permuted Activations for Interpolation Repair. ICLR Keller Jordan, Hanie Sedghi, Olga Saukh, Rahim Entezari, Behnam Neyshabur
2023	J	`jnl`	The Role of Pre-training Data in Transfer Learning. CoRR Rahim Entezari, Mitchell Wortsman, Olga Saukh, Moein Shariatnia, Hanie Sedghi, Ludwig Schmidt
2022	A*	`conf`	Exploring the Limits of Large Scale Pre-training. ICLR Samira Abnar, Mostafa Dehghani, Behnam Neyshabur, Hanie Sedghi
2022	J	`jnl`	Layer-Stack Temperature Scaling. CoRR Amr Khalifa, Michael C. Mozer, Hanie Sedghi, Behnam Neyshabur, Ibrahim Alabdulmohsin
2022	J	`jnl`	Leveraging Unlabeled Data to Predict Out-of-Distribution Performance. CoRR Saurabh Garg, Sivaraman Balakrishnan, Zachary C. Lipton, Behnam Neyshabur, Hanie Sedghi
2022	J	`jnl`	Leveraging Unlabeled Data to Track Memorization. CoRR Mahsa Forouzesh, Hanie Sedghi, Patrick Thiran
2022	A*	`conf`	Leveraging unlabeled data to predict out-of-distribution performance. ICLR Saurabh Garg, Sivaraman Balakrishnan, Zachary Chase Lipton, Behnam Neyshabur, Hanie Sedghi
2022	J	`jnl`	REPAIR: REnormalizing Permuted Activations for Interpolation Repair. CoRR Keller Jordan, Hanie Sedghi, Olga Saukh, Rahim Entezari, Behnam Neyshabur
2022	J	`jnl`	Teaching Algorithmic Reasoning via In-context Learning. CoRR Hattie Zhou, Azade Nova, Hugo Larochelle, Aaron C. Courville, Behnam Neyshabur, Hanie Sedghi
2022	A*	`conf`	The Role of Permutation Invariance in Linear Mode Connectivity of Neural Networks. ICLR Rahim Entezari, Hanie Sedghi, Olga Saukh, Behnam Neyshabur
2022	J	`jnl`	Understanding the effect of sparsity on neural networks robustness. CoRR Lukas Timpl, Rahim Entezari, Hanie Sedghi, Behnam Neyshabur, Olga Saukh
2021	J	`jnl`	Exploring the Limits of Large Scale Pre-training. CoRR Samira Abnar, Mostafa Dehghani, Behnam Neyshabur, Hanie Sedghi
2021	J	`jnl`	Gradual Domain Adaptation in the Wild: When Intermediate Distributions are Absent. CoRR Samira Abnar, Rianne van den Berg, Golnaz Ghiasi, Mostafa Dehghani, Nal Kalchbrenner, Hanie Sedghi
2021	A*	`conf`	The Deep Bootstrap Framework: Good Online Learners are Good Offline Generalizers. ICLR Preetum Nakkiran, Behnam Neyshabur, Hanie Sedghi
2021	J	`jnl`	The Role of Permutation Invariance in Linear Mode Connectivity of Neural Networks. CoRR Rahim Entezari, Hanie Sedghi, Olga Saukh, Behnam Neyshabur
2020	A*	`conf`	Generalization bounds for deep convolutional neural networks. ICLR Philip M. Long, Hanie Sedghi
2020	J	`jnl`	The Deep Bootstrap: Good Online Learners are Good Offline Generalizers. CoRR Preetum Nakkiran, Behnam Neyshabur, Hanie Sedghi
2020	A*	`conf`	The intriguing role of module criticality in the generalization of deep networks. ICLR Niladri S. Chatterji, Behnam Neyshabur, Hanie Sedghi
2020	A*	`conf`	What is being transferred in transfer learning? NeurIPS Behnam Neyshabur, Hanie Sedghi, Chiyuan Zhang
2020	J	`jnl`	What is being transferred in transfer learning? CoRR Behnam Neyshabur, Hanie Sedghi, Chiyuan Zhang
2019	J	`jnl`	On the Effect of the Activation Function on the Distribution of Hidden Nodes in a Deep Network. Neural Comput. Philip M. Long, Hanie Sedghi
2019	J	`jnl`	On the effect of the activation function on the distribution of hidden nodes in a deep network. CoRR Philip M. Long, Hanie Sedghi
2019	J	`jnl`	Size-free generalization bounds for convolutional neural networks. CoRR Philip M. Long, Hanie Sedghi
2019	J	`jnl`	SysML: The New Frontier of Machine Learning Systems. CoRR Alexander Ratner, Dan Alistarh, Gustavo Alonso, David G. Andersen, Peter Bailis, Sarah Bird, Nicholas Carlini, Bryan Catanzaro, Eric S. 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 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 Randall 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
2019	—	`conf`	The Singular Values of Convolutional Layers. ICLR (Poster) Hanie Sedghi, Vineet Gupta, Philip M. Long
2019	J	`jnl`	The intriguing role of module criticality in the generalization of deep networks. CoRR Niladri S. Chatterji, Behnam Neyshabur, Hanie Sedghi
2018	J	`jnl`	Knowledge Completion for Generics Using Guided Tensor Factorization. Trans. Assoc. Comput. Linguistics Hanie Sedghi, Ashish Sabharwal
2018	J	`jnl`	The Singular Values of Convolutional Layers. CoRR Hanie Sedghi, Vineet Gupta, Philip M. Long
2017	A	`conf`	How Good Are My Predictions? Efficiently Approximating Precision-Recall Curves for Massive Datasets. UAI Ashish Sabharwal, Hanie Sedghi
2016	J	`jnl`	Knowledge Completion for Generics using Guided Tensor Factorization. CoRR Hanie Sedghi, Ashish Sabharwal
2016	A	`conf`	Provable Tensor Methods for Learning Mixtures of Generalized Linear Models. AISTATS Hanie Sedghi, Majid Janzamin, Anima Anandkumar
2016	J	`jnl`	Training Input-Output Recurrent Neural Networks through Spectral Methods. CoRR Hanie Sedghi, Anima Anandkumar
2015	—	`conf`	FEAST at Play: Feature ExtrAction using Score function Tensors. FE@NIPS Majid Janzamin, Hanie Sedghi, U. N. Niranjan, Animashree Anandkumar
2015	J	`jnl`	Generalization Bounds for Neural Networks through Tensor Factorization. CoRR Majid Janzamin, Hanie Sedghi, Anima Anandkumar
2015	J	`jnl`	Learning Mixed Membership Community Models in Social Tagging Networks through Tensor Methods. CoRR Anima Anandkumar, Hanie Sedghi
2015	—	`conf`	Provable Methods for Training Neural Networks with Sparse Connectivity. ICLR (Workshop) Hanie Sedghi, Anima Anandkumar
2015	—	`conf`	Score Function Features for Discriminative Learning. ICLR (Workshop) Majid Janzamin, Hanie Sedghi, Anima Anandkumar
2015	J	`jnl`	Statistical Structure Learning to Ensure Data Integrity in Smart Grid. IEEE Trans. Smart Grid Hanie Sedghi, Edmond A. Jonckheere
2014	J	`jnl`	Guarantees for Multi-Step Stochastic ADMM in High Dimensions. CoRR Hanie Sedghi, Anima Anandkumar, Edmond A. Jonckheere
2014	—	`conf`	Multi-Step Stochastic ADMM in High Dimensions: Applications to Sparse Optimization and Matrix Decomposition. NIPS Hanie Sedghi, Anima Anandkumar, Edmond A. Jonckheere
2014	J	`jnl`	Provable Tensor Methods for Learning Mixtures of Classifiers. CoRR Hanie Sedghi, Anima Anandkumar
2014	J	`jnl`	Score Function Features for Discriminative Learning: Matrix and Tensor Framework. CoRR Majid Janzamin, Hanie Sedghi, Anima Anandkumar
2014	J	`jnl`	Statistical Structure Learning, Towards a Robust Smart Grid. CoRR Hanie Sedghi, Edmond A. Jonckheere
2010	B	`conf`	A Game-Theoretic Approach for Power Allocation in Bidirectional Cooperative Communication. WCNC Majid Janzamin, Mohammad Reza Pakravan, Hanie Sedghi