NIPS Proceedingsβ

Babak Hassibi

12 Papers

  • The Impact of Regularization on High-dimensional Logistic Regression (2019)
  • Universality in Learning from Linear Measurements (2019)
  • Learning without the Phase: Regularized PhaseMax Achieves Optimal Sample Complexity (2018)
  • A Universal Analysis of Large-Scale Regularized Least Squares Solutions (2017)
  • Crowdsourced Clustering: Querying Edges vs Triangles (2016)
  • Fundamental Limits of Budget-Fidelity Trade-off in Label Crowdsourcing (2016)
  • LASSO with Non-linear Measurements is Equivalent to One With Linear Measurements (2015)
  • Graph Clustering With Missing Data: Convex Algorithms and Analysis (2014)
  • H∞ Optimal Training Algorithms and their Relation to Backpropagation (1994)
  • Hoo Optimality Criteria for LMS and Backpropagation (1993)
  • Optimal Brain Surgeon: Extensions and performance comparisons (1993)
  • Second order derivatives for network pruning: Optimal Brain Surgeon (1992)