Preetum Nakkiran
Publication record assembled from the DBLP archive of ranked conferences.
Papers indexed
20
Venues
10
Active years
2014–2025
Best venue rank
A*
Where they publish
Papers
20 indexed papers, newest first.
| Year | Venue | Title | Authors |
|---|---|---|---|
| 2025 | AISTATS | Composition and Control with Distilled Energy Diffusion Models and Sequential Monte Carlo. | James Thornton, Louis Bthune, Ruixiang Zhang, Arwen Bradley, Preetum Nakkiran, Shuangfei Zhai |
| 2025 | ICLR | A Formal Framework for Understanding Length Generalization in Transformers. | Xinting Huang, Andy Yang, Satwik Bhattamishra, Yash Raj Sarrof, Andreas Krebs, Hattie Zhou, Preetum Nakkiran, Michael Hahn |
| 2025 | ICML | Mechanisms of Projective Composition of Diffusion Models. | Arwen Bradley, Preetum Nakkiran, David Berthelot, James Thornton, Joshua M. Susskind |
| 2025 | ICML | Normalizing Flows are Capable Generative Models. | Shuangfei Zhai, Ruixiang Zhang, Preetum Nakkiran, David Berthelot, Jiatao Gu, Huangjie Zheng, Tianrong Chen, Miguel ngel Bautista, Navdeep Jaitly, Joshua M. Susskind |
| 2024 | ICLR | Smooth ECE: Principled Reliability Diagrams via Kernel Smoothing. | Jaroslaw Blasiok, Preetum Nakkiran |
| 2024 | ICLR | Vanishing Gradients in Reinforcement Finetuning of Language Models. | Noam Razin, Hattie Zhou, Omid Saremi, Vimal Thilak, Arwen Bradley, Preetum Nakkiran, Joshua M. Susskind, Etai Littwin |
| 2024 | ICLR | LiDAR: Sensing Linear Probing Performance in Joint Embedding SSL Architectures. | Vimal Thilak, Chen Huang, Omid Saremi, Laurent Dinh, Hanlin Goh, Preetum Nakkiran, Joshua M. Susskind, Etai Littwin |
| 2024 | ICLR | What Algorithms can Transformers Learn? A Study in Length Generalization. | Hattie Zhou, Arwen Bradley, Etai Littwin, Noam Razin, Omid Saremi, Joshua M. Susskind, Samy Bengio, Preetum Nakkiran |
| 2023 | ICLR | Deconstructing Distributions: A Pointwise Framework of Learning. | Gal Kaplun, Nikhil Ghosh, Saurabh Garg, Boaz Barak, Preetum Nakkiran |
| 2023 | STOC | A Unifying Theory of Distance from Calibration. | Jaroslaw Blasiok, Parikshit Gopalan, Lunjia Hu, Preetum Nakkiran |
| 2021 | ICLR | The Deep Bootstrap Framework: Good Online Learners are Good Offline Generalizers. | Preetum Nakkiran, Behnam Neyshabur, Hanie Sedghi |
| 2021 | ICLR | Optimal Regularization can Mitigate Double Descent. | Preetum Nakkiran, Prayaag Venkat, Sham M. Kakade, Tengyu Ma |
| 2020 | ICLR | Deep Double Descent: Where Bigger Models and More Data Hurt. | Preetum Nakkiran, Gal Kaplun, Yamini Bansal, Tristan Yang, Boaz Barak, Ilya Sutskever |
| 2019 | COLT | Computational Limitations in Robust Classification and Win-Win Results. | Akshay Degwekar, Preetum Nakkiran, Vinod Vaikuntanathan |
| 2018 | STOC | General strong polarization. | Jaroslaw Blasiok, Venkatesan Guruswami, Preetum Nakkiran, Atri Rudra, Madhu Sudan |
| 2016 | ISIT | Optimal systematic distributed storage codes with fast encoding. | Preetum Nakkiran, K. V. Rashmi, Kannan Ramchandran |
| 2015 | FAST | Having Your Cake and Eating It Too: Jointly Optimal Erasure Codes for I/O, Storage, and Network-bandwidth. | K. V. Rashmi, Preetum Nakkiran, Jingyan Wang, Nihar B. Shah, Kannan Ramchandran |
| 2015 | ICASSP | Automatic gain control and multi-style training for robust small-footprint keyword spotting with deep neural networks. | Rohit Prabhavalkar, Raziel Alvarez, Carolina Parada, Preetum Nakkiran, Tara N. Sainath |
| 2015 | Interspeech | Compressing deep neural networks using a rank-constrained topology. | Preetum Nakkiran, Raziel Alvarez, Rohit Prabhavalkar, Carolina Parada |
| 2014 | GLOBECOM | Fundamental limits on communication for oblivious updates in storage networks. | Preetum Nakkiran, Nihar B. Shah, K. V. Rashmi |