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Jason D. Lee

Identifiers

  • name variant Jason D. Lee 0.60 · backfill

Papers (39)

  1. Fine-Tuning Dynamics of In-Context Factual Recall in Transformers cs.LG · 2026 · author #3
  2. Sharp Capacity Thresholds in Linear Associative Memory: From Winner-Take-All to Listwise Retrieval stat.ML · 2026 · author #4
  3. The Power of Power Law: Asymmetry Enables Compositional Reasoning cs.AI · 2026 · author #3
  4. Sharp Capacity Scaling of Spectral Optimizers in Learning Associative Memory cs.LG · 2026 · author #5
  5. Discrepancies are Virtue: Weak-to-Strong Generalization through Lens of Intrinsic Dimension cs.LG · 2025 · author #4
  6. Medusa: Simple LLM Inference Acceleration Framework with Multiple Decoding Heads cs.LG · 2024 · author #5
  7. Lexicographic and Depth-Sensitive Margins in Homogeneous and Non-Homogeneous Deep Models stat.ML · 2019 · author #3
  8. Solving Non-Convex Non-Concave Min-Max Games Under Polyak-{\L}ojasiewicz Condition math.OC · 2018 · author #3
  9. Gradient Descent Finds Global Minima of Deep Neural Networks cs.LG · 2018 · author #2
  10. Provably Correct Automatic Subdifferentiation for Qualified Programs math.OC · 2018 · author #2
  11. Algorithmic Regularization in Learning Deep Homogeneous Models: Layers are Automatically Balanced cs.LG · 2018 · author #3
  12. Adding One Neuron Can Eliminate All Bad Local Minima stat.ML · 2018 · author #3
  13. Stochastic subgradient method converges on tame functions math.OC · 2018 · author #4
  14. Convergence of Gradient Descent on Separable Data stat.ML · 2018 · author #2
  15. On the Power of Over-parametrization in Neural Networks with Quadratic Activation cs.LG · 2018 · author #2
  16. Gradient Primal-Dual Algorithm Converges to Second-Order Stationary Solutions for Nonconvex Distributed Optimization math.OC · 2018 · author #2
  17. On the Convergence and Robustness of Training GANs with Regularized Optimal Transport cs.LG · 2018 · author #4
  18. Gradient Descent Learns One-hidden-layer CNN: Don't be Afraid of Spurious Local Minima cs.LG · 2017 · author #2
  19. Learning One-hidden-layer Neural Networks with Landscape Design cs.LG · 2017 · author #2
  20. First-order Methods Almost Always Avoid Saddle Points stat.ML · 2017 · author #1
  21. When is a Convolutional Filter Easy To Learn? cs.LG · 2017 · author #2
  22. An inexact subsampled proximal Newton-type method for large-scale machine learning cs.LG · 2017 · author #3
  23. Gradient Descent Can Take Exponential Time to Escape Saddle Points math.OC · 2017 · author #3
  24. Black-box Importance Sampling stat.ML · 2016 · author #2
  25. Sketching Meets Random Projection in the Dual: A Provable Recovery Algorithm for Big and High-dimensional Data cs.LG · 2016 · author #2
  26. Communication-Efficient Distributed Statistical Inference stat.ML · 2016 · author #2
  27. Matrix Completion has No Spurious Local Minimum cs.LG · 2016 · author #2
  28. Gradient Descent Converges to Minimizers stat.ML · 2016 · author #1
  29. A Kernelized Stein Discrepancy for Goodness-of-fit Tests and Model Evaluation stat.ML · 2016 · author #2
  30. Learning Halfspaces and Neural Networks with Random Initialization cs.LG · 2015 · author #2
  31. $\ell_1$-regularized Neural Networks are Improperly Learnable in Polynomial Time cs.LG · 2015 · author #2
  32. Distributed Stochastic Variance Reduced Gradient Methods and A Lower Bound for Communication Complexity math.OC · 2015 · author #1
  33. Selective Inference and Learning Mixed Graphical Models stat.ML · 2015 · author #1
  34. Communication-efficient sparse regression: a one-shot approach stat.ML · 2015 · author #1
  35. Scalable methods for nonnegative matrix factorizations of near-separable tall-and-skinny matrices cs.LG · 2014 · author #2
  36. Exact post-selection inference, with application to the lasso math.ST · 2013 · author #1
  37. On model selection consistency of regularized M-estimators math.ST · 2013 · author #1
  38. Proximal Newton-type methods for minimizing composite functions stat.ML · 2012 · author #1
  39. Learning Mixed Graphical Models stat.ML · 2012 · author #1

Mentions

  • 1402.6964 #2 · backfill · confidence 0.70 Jason D. Lee
  • 1311.6238 #1 · backfill · confidence 0.70 Jason D. Lee
  • 2605.27774 #3 · arxiv_oai · confidence 0.70 Jason D. Lee
  • 1305.7477 #1 · backfill · confidence 0.70 Jason D. Lee
  • 1206.1623 #1 · backfill · confidence 0.70 Jason D. Lee
  • 1205.5012 #1 · backfill · confidence 0.70 Jason D. Lee

Frequent Coauthors