Papers
Discriminative Learning of Prediction Intervals
Nir Rosenfeld, Yishay Mansour, Elad Yom-Tov
Semi-Supervised Learning with Competitive Infection Models
Nir Rosenfeld, Amir Globerson
Optimal Submodular Extensions for Marginal Estimation
Pankaj Pansari, Chris Russell, M Pawan Kumar
Factorial HMMs with Collapsed Gibbs Sampling for Optimizing Long-term HIV Therapy
Amit Gruber, Chen Yanover, Tal El-Hay et al.
Robust Active Label Correction
Jan Kremer, Fei Sha, Christian Igel
High-Dimensional Bayesian Optimization via Additive Models with Overlapping Groups
Paul Rolland, Jonathan Scarlett, Ilija Bogunovic et al.
Zeroth-Order Online Alternating Direction Method of Multipliers: Convergence Analysis and Applications
Sijia Liu, Jie Chen, Pin-Yu Chen et al.
Online Boosting Algorithms for Multi-label Ranking
Young Hun Jung, Ambuj Tewari
Riemannian stochastic quasi-Newton algorithm with variance reduction and its convergence analysis
Hiroyuki Kasai, Hiroyuki Sato, Bamdev Mishra
Nonlinear Structured Signal Estimation in High Dimensions via Iterative Hard Thresholding
Kaiqing Zhang, Zhuoran Yang, Zhaoran Wang
Learning Determinantal Point Processes in Sublinear Time
Christophe Dupuy, Francis Bach
Online Learning with Non-Convex Losses and Non-Stationary Regret
Xiand Gao, Xiaobo Li, Shuzhong Zhang
AdaGeo: Adaptive Geometric Learning for Optimization and Sampling
Gabriele Abbati, Alessandra Tosi, Michael Osborne et al.
Integral Transforms from Finite Data: An Application of Gaussian Process Regression to Fourier Analysis
Luca Ambrogioni, Eric Maris
Outlier Detection and Robust Estimation in Nonparametric Regression
Dehan Kong, Howard Bondell, Weining Shen
Finding Global Optima in Nonconvex Stochastic Semidefinite Optimization with Variance Reduction
Jinshan Zeng, Ke Ma, Yuan Yao
IHT dies hard: Provable accelerated Iterative Hard Thresholding
Rajiv Khanna, Anastasios Kyrillidis
Layerwise Systematic Scan: Deep Boltzmann Machines and Beyond
Heng Guo, Kaan Kara, Ce Zhang
On Truly Block Eigensolvers via Riemannian Optimization
Zhiqiang Xu, Xin Gao
Post Selection Inference with Kernels
Makoto Yamada, Yuta Umezu, Kenji Fukumizu et al.
On the challenges of learning with inference networks on sparse, high-dimensional data
Rahul Krishnan, Dawen Liang, Matthew Hoffman
Parallelised Bayesian Optimisation via Thompson Sampling
Kirthevasan Kandasamy, Akshay Krishnamurthy, Jeff Schneider et al.
Can clustering scale sublinearly with its clusters? A variational EM acceleration of GMMs and k-means
Dennis Forster, Jörg Lücke
Iterative Spectral Method for Alternative Clustering
Chieh Wu, Stratis Ioannidis, Mario Sznaier et al.