Dr Sergio Bacallado

Name:	Dr Sergio Bacallado
Affiliation:
E-mail:	(only provided to users who are logged into talks.cam)
Last login:	18 Apr 2024, 9:16 p.m.

Public lists managed by Dr Sergio Bacallado

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Talks given by Dr Sergio Bacallado

Obviously this only lists talks that are listed through talks.cam. Furthermore, this facility only works if the speaker's e-mail was specified in a talk. Most talks have not done this.

• A Bayesian ordination method for 16S microbiome profiling data
• A Bayesian ordination method for 16S microbiome profiling data
• A Bayesian ordination method for 16S microbiome profiling data
• Title to be confirmed

Talks organised by Dr Sergio Bacallado

This list is based on what was entered into the 'organiser' field in a talk. It may not mean that Dr Sergio Bacallado actually organised the talk, they may have been responsible only for entering the talk into the talks.cam system.

• Nonparametric classification with missing data
• Oja's algorithm for sparse PCA
• Learning with latent symmetries
• On Independent Samples along the Langevin Dynamics and Algorithm
• On optimal ranking in crowd-sourcing problems in several scenarios
• Rates of convergence for tensor denoising
• Spatial causal inference in the presence of unmeasured confounding and interference
• Quantitative Uniform Stability of the Iterative Proportional Fitting Procedure
• Concentration and Free Probability
• Barycentric subspace analysis for sets of unlabeled graphs
• Compressed sensing for the sparse Radon transform
• Robust density estimation and model selection for the L1 loss : Applications to shape-constrained density estimation.
• M-estimation, noisy optimization and user-level local privacy
• Response-adaptive randomization in clinical trials: from myths to practical considerations
• Non-asymptotic control of a kernel 2-sample test
• Title to be confirmed
• Distribution-free inference for regression: discrete, continuous, and in between
• Distribution-Free Nonparametric Inference Based on Optimal Transport: Efficiency Lower Bounds and Rank-Kernel Tests
• Correlated randomly growing graphs
• Recent progress on the KLS conjecture and Eldan’s stochastic localization scheme
• Functional Models for Time Varying Random Objects
• Seminar Cancelled
• Optimal rates for independence testing via U-statistic permutation tests
• Distribution-Free, Risk-Controlling Prediction Sets
• A precise high-dimensional asymptotic theory for Adaboost
• Generalized Kernel Two-Sample Tests
• Provable representation learning in deep learning
• Minimax estimation of smooth densities in Wasserstein distance
• Title to be confirmed
• Model selection for estimation of causal parameters
• Title to be confirmed
• Title to be confirmed
• Title to be confirmed
• Implicit Regularization for Optimal Sparse Recovery
• Improved Nonparametric Empirical Bayes Estimation using Transfer Learning
• Network Representation Using Graph Root Distributions
• Neyman-Pearson Classification
• Spillover Effects in Cluster Randomized Trials with Noncompliance
• Langevin Monte Carlo for Degenerately Convex Potentials
• Network change point detection
• Selection bias, missing data and causal inference
• Title to be confirmed
• The concept of separable effects for causal mediation and competing risks analyses
• Title to be confirmed
• Posterior contraction rates for potentially nonlinear inverse problems
• On Statistical Learning for Individualized Decision Making with Complex Data
• Title to be confirmed
• Convergence of Gaussian process emulators with estimated hyper-parameters and applications in Bayesian inverse problems
• Title to be confirmed
• Optimal Transport: Fast Probabilistic Approximation with Exact Solvers
• Approximate Cross Validation for Large Data and High Dimensions
• On the convergence of the Hamiltonian Monte Carlo algorithm and other irreversible MCMC methods
• Optimal Transport for Machine Learning
• Multiscale Analysis of Bayesian CART
• Identifying Cointegration by Eigenanalysis
• Title to be confirmed
• Classification with unknown class conditional label noise on non-compact feature spaces
• On Estimation of Unnormalized Density Models
• Title to be confirmed
• Asymptotic normality of certain transformation averages
• On the robustness of gradient-based MCMC algorithms
• Regularized linear autoencoders, the Morse theory of loss, and backprop in the brain
• Geometrizing rates of convergence under local differential privacy
• Recent Developments in the Study of Single-Index Type Models
• Nonparametric maximum likelihood methods for binary response models with random coefficients
• MAP estimators and posterior consistency for Bayesian inverse problems with exponential priors
• Title to be confirmed
• On distributed Bayesian computation
• On the Consistency of Supervised Learning with Missing Values
• Nuisance parameters
• Explicit stabilised Runge-Kutta methods and their application to Bayesian inverse problems
• Analysis of Networks via the Sparse β-Model
• High-dimensional sign tests for the direction of a skewed single-spiked distribution
• On the fundamental understanding of distributed computation
• Post-selection confidence intervals and confidence curves
• Model selection with Lasso-Zero and a robust extension with an application to the problem of missing covariates
• Geometric MCMC for infinite-dimensional Bayesian Inverse Problems
• On the hypocoercivity of some PDMP-Monte Carlo algorithms
• Posterior concentration for Bayesian regression trees and their ensembles
• Concentration of tempered posteriors and of their variational approximations
• Phase transitions on community detectability for various types of stochastic block models
• Towards a better understanding of early stopping for boosting algorithms
• Bayesian regression models for complex spatially or serially correlated functional data
• Nonparametric Bayes for support boundary recovery
• Uniform rates of Glivenko-Cantelli convergence and their use in Bayesian inference
• Heteroskedastic PCA: Algorithm, Optimality, and Applications