NIPS Proceedingsβ

Pradeep K. Ravikumar

23 Papers

  • Dual Decomposed Learning with Factorwise Oracle for Structural SVM of Large Output Domain (2016)
  • Beyond Sub-Gaussian Measurements: High-Dimensional Structured Estimation with Sub-Exponential Designs (2015)
  • Closed-form Estimators for High-dimensional Generalized Linear Models (2015)
  • Collaborative Filtering with Graph Information: Consistency and Scalable Methods (2015)
  • Consistent Multilabel Classification (2015)
  • Fast Classification Rates for High-dimensional Gaussian Generative Models (2015)
  • Fixed-Length Poisson MRF: Adding Dependencies to the Multinomial (2015)
  • Sparse Linear Programming via Primal and Dual Augmented Coordinate Descent (2015)
  • A Representation Theory for Ranking Functions (2014)
  • Capturing Semantically Meaningful Word Dependencies with an Admixture of Poisson MRFs (2014)
  • Consistent Binary Classification with Generalized Performance Metrics (2014)
  • Constant Nullspace Strong Convexity and Fast Convergence of Proximal Methods under High-Dimensional Settings (2014)
  • Elementary Estimators for Graphical Models (2014)
  • On the Information Theoretic Limits of Learning Ising Models (2014)
  • Proximal Quasi-Newton for Computationally Intensive L1-regularized M-estimators (2014)
  • QUIC & DIRTY: A Quadratic Approximation Approach for Dirty Statistical Models (2014)
  • Sparse Random Feature Algorithm as Coordinate Descent in Hilbert Space (2014)
  • BIG & QUIC: Sparse Inverse Covariance Estimation for a Million Variables (2013)
  • Conditional Random Fields via Univariate Exponential Families (2013)
  • Dirty Statistical Models (2013)
  • Large Scale Distributed Sparse Precision Estimation (2013)
  • Learning with Noisy Labels (2013)
  • On Poisson Graphical Models (2013)