Active Learning for Contextual Search with Binary Feedback
In this paper, we study the learning problem in contextual search, which is motivated by applications such as crowdsourcing and personalized medicine experiments. In particular, for a sequence of a…
GigaMVS : A Benchmark for Ultra-Large-Scale Gigapixel-Level 3D Reconstruction
Multiview stereopsis (MVS) methods, which can reconstruct both the 3D geometry and texture from multiple images, have been rapidly developed and extensively investigated from the feature engineerin…
Bandwidth Characteristics of Mid-Wavelength Infrared PIN HgCdTe Avalanche Pho…
HgCdTe avalanche photodiodes (APDs) are used in mid-wavelength infrared (MWIR) photoelectric detectors in free-space optical communication, three-dimensional light detection, and ranging. Although …
Differential Privacy in Personalized Pricing with Nonparametric Demand Models
In recent decades, the advance of information technology and abundant personal data facilitate the application of algorithmic personalized pricing. However, this leads to the growing concern of pot…
Locating and Counting Heads in Crowds With a Depth Prior
To simultaneously estimate the number of heads and locate heads with bounding boxes, we resort to detection-based crowd counting by leveraging RGB-D data and design a dual-path guided detection net…
Single-modulator Based Multi-Format Switchable Signal Generator Without Backg…
A photonic multi-format background-free binarily modulated microwave signal generator using a single dual-polarization dual-parallel Mach–Zehnder modulator is proposed and demonstrated. The propo…
A Simple Spectral Failure Mode for Graph Convolutional Networks
Neural networks have achieved remarkable successes in machine learning tasks. This has recently been extended to graph learning using neural networks. However, there is limited theoretical work in …
Unsupervised Learning-Driven Matheuristic for Production-Distribution Problems
In this paper, we study a capacitated production-distribution problem where facility location, production, and distribution decisions are tightly coupled and simultaneously considered in the optima…
Inference of Breakpoints in High-dimensional Time Series
For multiple change-points detection of high-dimensional time series, we provide asymptotic theory concerning the consistency and the asymptotic distribution of the breakpoint statistics and estima…
A Primal–Dual Learning Algorithm for Personalized Dynamic Pricing with an I…
We consider the problem of a firm seeking to use personalized pricing to sell an exogenously given stock of a product over a finite selling horizon to different consumer types. We assume that the t…
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