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Found 11 papers, 1 papers with code
Swarm of Robotic Aerial Base Stations for mmWave Multi-Hop Backhauling
Robotic aerial base stations (RABSs) that are able to anchor at tall urban landforms are expected to bring further flexibility to millimeter-wave (mmWave) multi-hop backhaul networks in highly dense urban environments.
Economic Forecasts Using Many Noises
This paper addresses a key question in economic forecasting: does pure noise truly lack predictive power?
Inference for Low-rank Models without Estimating the Rank
This paper studies the inference about linear functionals of high-dimensional low-rank matrices.
SGMM: Stochastic Approximation to Generalized Method of Moments
We introduce a new class of algorithms, Stochastic Generalized Method of Moments (SGMM), for estimation and inference on (overidentified) moment restriction models.
Inference for Low-rank Completion without Sample Splitting with Application to Treatment Effect Estimation
This paper studies the inferential theory for estimating low-rank matrices.
Inference on Time Series Nonparametric Conditional Moment Restrictions Using General Sieves
This paper considers general nonlinear sieve quasi-likelihood ratio (GN-QLR) based inference on expectation functionals of time series data, where the functionals of interest are based on some nonparametric function that satisfy conditional moment restrictions and are learned using multilayer neural networks.
Fast Inference for Quantile Regression with Tens of Millions of Observations
Big data analytics has opened new avenues in economic research, but the challenge of analyzing datasets with tens of millions of observations is substantial.
Dynamic Heterogeneous Distribution Regression Panel Models, with an Application to Labor Income Processes
We first quantify the impact of a negative labor income shock on the distribution of future labor income.
Fast and Robust Online Inference with Stochastic Gradient Descent via Random Scaling
We develop a new method of online inference for a vector of parameters estimated by the Polyak-Ruppert averaging procedure of stochastic gradient descent (SGD) algorithms.
Recent Developments on Factor Models and its Applications in Econometric Learning
This paper makes a selective survey on the recent development of the factor model and its application on statistical learnings.
Mutual Enhancement for Detection of Multiple Logos in Sports Videos
Mutual enhancement is also included in our frame propagation mechanism that improves logo detection by utilizing the continuity of logos across frames.
