Search Results for author: Sifan Liu

Found 10 papers, 2 papers with code

Black-box Selective Inference via Bootstrapping

no code implementations28 Mar 2022 Sifan Liu, Jelena Markovic-Voronov, Jonathan Taylor

Conditional selective inference requires an exact characterization of the selection event, which is often unavailable except for a few examples like the lasso.

Model Selection

BS-RIS-User Association and Beamforming Designs for RIS-aided Cellular Networks

no code implementations27 Jun 2021 Sifan Liu, Pengfei Ni, Rang Liu, Yang Liu, Ming Li, Qian Liu

During the dynamical access process, an iterative algorithm is proposed to alternatively obtain the active and passive beamforming.

Quasi-Newton Quasi-Monte Carlo for variational Bayes

no code implementations7 Apr 2021 Sifan Liu, Art B. Owen

Many machine learning problems optimize an objective that must be measured with noise.

Second-order methods

Global and Individualized Community Detection in Inhomogeneous Multilayer Networks

no code implementations2 Dec 2020 Shuxiao Chen, Sifan Liu, Zongming Ma

Focusing on the symmetric two block case, we establish minimax rates for both global estimation of the common structure and individualized estimation of layer-wise community structures.

Community Detection

Optimal Iterative Sketching Methods with the Subsampled Randomized Hadamard Transform

no code implementations NeurIPS 2020 Jonathan Lacotte, Sifan Liu, Edgar Dobriban, Mert Pilanci

These show that the convergence rate for Haar and randomized Hadamard matrices are identical, and asymptotically improve upon Gaussian random projections.

Dimensionality Reduction

Optimal Iterative Sketching with the Subsampled Randomized Hadamard Transform

no code implementations3 Feb 2020 Jonathan Lacotte, Sifan Liu, Edgar Dobriban, Mert Pilanci

These show that the convergence rate for Haar and randomized Hadamard matrices are identical, and asymptotically improve upon Gaussian random projections.

Dimensionality Reduction

Asymptotics for Sketching in Least Squares Regression

1 code implementation NeurIPS 2019 Edgar Dobriban, Sifan Liu

We consider a least squares regression problem where the data has been generated from a linear model, and we are interested to learn the unknown regression parameters.

Dimensionality Reduction regression

Error Detection in a Large-Scale Lexical Taxonomy

no code implementations5 Aug 2018 Sifan Liu, Hongzhi Wang

Motived by this, we measure the relation of two concepts by the distance between their corresponding instances and detect errors within the intersection of the conflicting concept sets.

Relation

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