Papers
8,340 papers found
Gradient Hard Thresholding Pursuit for Sparsity-Constrained Optimization
Xiaotong Yuan, Ping Li, Tong Zhang
Graph-based Semi-supervised Learning: Realizing Pointwise Smoothness Probabilistically
Yuan Fang, Kevin Chang, Hady Lauw
Guess-Averse Loss Functions For Cost-Sensitive Multiclass Boosting
Oscar Beijbom, Mohammad Saberian, David Kriegman et al.
Hamiltonian Monte Carlo Without Detailed Balance
Jascha Sohl-Dickstein, Mayur Mudigonda, Michael DeWeese
Hard-Margin Active Linear Regression
Elad Hazan, Zohar Karnin
Heavy-tailed regression with a generalized median-of-means
Daniel Hsu, Sivan Sabato
Hierarchical Conditional Random Fields for Outlier Detection: An Application to Detecting Epileptogenic Cortical Malformations
Bilal Ahmed, Thomas Thesen, Karen Blackmon et al.
Hierarchical Dirichlet Scaling Process
Dongwoo Kim, Alice Oh
Hierarchical Quasi-Clustering Methods for Asymmetric Networks
Gunnar Carlsson, Facundo Mémoli, Alejandro Ribeiro et al.
High Order Regularization for Semi-Supervised Learning of Structured Output Problems
Yujia Li, Rich Zemel
Improving offline evaluation of contextual bandit algorithms via bootstrapping techniques
Jérémie Mary, Philippe Preux, Olivier Nicol
Inferning with High Girth Graphical Models
Uri Heinemann, Amir Globerson
Influence Function Learning in Information Diffusion Networks
Nan Du, Yingyu Liang, Maria Balcan et al.
Input Warping for Bayesian Optimization of Non-Stationary Functions
Jasper Snoek, Kevin Swersky, Rich Zemel et al.
Joint Inference of Multiple Label Types in Large Networks
Deepayan Chakrabarti, Stanislav Funiak, Jonathan Chang et al.
Kernel Adaptive Metropolis-Hastings
Dino Sejdinovic, Heiko Strathmann, Maria Lomeli Garcia et al.
Kernel Mean Estimation and Stein Effect
Krikamol Muandet, Kenji Fukumizu, Bharath Sriperumbudur et al.
K-means recovers ICA filters when independent components are sparse
Alon Vinnikov, Shai Shalev-Shwartz
Large-Margin Metric Learning for Constrained Partitioning Problems
Rémi Lajugie, Francis Bach, Sylvain Arlot
Large-margin Weakly Supervised Dimensionality Reduction
Chang Xu, Dacheng Tao, Chao Xu et al.
Large-scale Multi-label Learning with Missing Labels
Hsiang-Fu Yu, Prateek Jain, Purushottam Kar et al.
Latent Bandits.
Odalric-Ambrym Maillard, Shie Mannor
Latent Confusion Analysis by Normalized Gamma Construction
Issei Sato, Hisashi Kashima, Hiroshi Nakagawa
Latent Semantic Representation Learning for Scene Classification
Xin Li, Yuhong Guo
Latent Variable Copula Inference for Bundle Pricing from Retail Transaction Data
Benjamin Letham, Wei Sun, Anshul Sheopuri