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Found 5 papers, 1 papers with code
Towards a Complete Analysis of Langevin Monte Carlo: Beyond Poincaré Inequality
We do so by establishing upper and lower bounds for Langevin diffusions and LMC under weak Poincar\'e inequalities that are satisfied by a large class of densities including polynomially-decaying heavy-tailed densities (i. e., Cauchy-type).
Mean-Square Analysis of Discretized Itô Diffusions for Heavy-tailed Sampling
We analyze the complexity of sampling from a class of heavy-tailed distributions by discretizing a natural class of It\^o diffusions associated with weighted Poincar\'e inequalities.
Generalisation under gradient descent via deterministic PAC-Bayes
We establish disintegrated PAC-Bayesian generalisation bounds for models trained with gradient descent methods or continuous gradient flows.
Time-independent Generalization Bounds for SGLD in Non-convex Settings
We establish generalization error bounds for stochastic gradient Langevin dynamics (SGLD) with constant learning rate under the assumptions of dissipativity and smoothness, a setting that has received increased attention in the sampling/optimization literature.
Span-ConveRT: Few-shot Span Extraction for Dialog with Pretrained Conversational Representations
We introduce Span-ConveRT, a light-weight model for dialog slot-filling which frames the task as a turn-based span extraction task.
