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Theory

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Papers

Exploration of the (Non-)Asymptotic Bias and Variance of Stochastic Gradient Langevin Dynamics JMLR 2016
Double or Nothing: Multiplicative Incentive Mechanisms for Crowdsourcing JMLR 2016
The Asymptotic Performance of Linear Echo State Neural Networks JMLR 2016
Guarding against Spurious Discoveries in High Dimensions JMLR 2016
ERRATA: On the Estimation of the Gradient Lines of a Density and the Consistency of the Mean-Shift Algorithm JMLR 2016
On Bayes Risk Lower Bounds JMLR 2016
A Characterization of Linkage-Based Hierarchical Clustering JMLR 2016
Efficient Network Reachability Analysis Using a Succinct Control Plane Representation OSDI 2016
XFT: Practical Fault Tolerance beyond Crashes OSDI 2016
The Parameterized Complexity of Approximate Inference in Bayesian Networks PGM 2016
The Effect of Combination Functions on the Complexity of Relational Bayesian Networks PGM 2016
Set-labelled filters and sensor transformations RSS 2016
LASSO with Non-linear Measurements is Equivalent to One With Linear Measurements NIPS 2015
Sample Complexity of Episodic Fixed-Horizon Reinforcement Learning NIPS 2015
Precision-Recall-Gain Curves: PR Analysis Done Right NIPS 2015
Empirical Localization of Homogeneous Divergences on Discrete Sample Spaces NIPS 2015
Information-theoretic lower bounds for convex optimization with erroneous oracles NIPS 2015
The Consistency of Common Neighbors for Link Prediction in Stochastic Blockmodels NIPS 2015
On the Accuracy of Self-Normalized Log-Linear Models NIPS 2015
Learnability of Influence in Networks NIPS 2015
Calibrated Structured Prediction NIPS 2015
Fighting Bandits with a New Kind of Smoothness NIPS 2015
Algorithmic Stability and Uniform Generalization NIPS 2015
The Pareto Regret Frontier for Bandits NIPS 2015
Sample Complexity of Learning Mahalanobis Distance Metrics NIPS 2015