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Found 9 papers, 2 papers with code
Near-optimal inference in adaptive linear regression
We propose a family of online debiasing estimators to correct these distributional anomalies in least squares estimation.
VisualSem: A High-quality Knowledge Graph for Vision and Language
We also release a neural multi-modal retrieval model that can use images or sentences as inputs and retrieves entities in the KG.
Online Debiasing for Adaptively Collected High-dimensional Data with Applications to Time Series Analysis
Adaptive collection of data is commonplace in applications throughout science and engineering.
Contextual Stochastic Block Models
We provide the first information theoretic tight analysis for inference of latent community structure given a sparse graph along with high dimensional node covariates, correlated with the same latent communities.
Accurate Inference for Adaptive Linear Models
Estimators computed from adaptively collected data do not behave like their non-adaptive brethren.
Inference in Graphical Models via Semidefinite Programming Hierarchies
We demonstrate that the resulting algorithm can solve problems with tens of thousands of variables within minutes, and outperforms BP and GBP on practical problems such as image denoising and Ising spin glasses.
Improved Sum-of-Squares Lower Bounds for Hidden Clique and Hidden Submatrix Problems
Here we consider the degree-$4$ SOS relaxation, and study the construction of \cite{meka2013association} to prove that SOS fails unless $k\ge C\, n^{1/3}/\log n$.
Cone-Constrained Principal Component Analysis
We consider a simple model for noisy quadratic observation of an unknown vector $\bvz$.
Sparse PCA via Covariance Thresholding
In an influential paper, \cite{johnstone2004sparse} introduced a simple algorithm that estimates the support of the principal vectors $\mathbf{v}_1,\dots,\mathbf{v}_r$ by the largest entries in the diagonal of the empirical covariance.
