In this paper, we provide the first computationally and statistically efficient estimators for truncated linear regression when the noise variance is unknown, estimating both the linear model and the variance of the noise.
This paper derives the generalized extreme value (GEV) model with implicit availability/perception (IAP) of alternatives and proposes a variational autoencoder (VAE) approach for choice set generation and implicit perception of alternatives.
Frequency-constrained unit commitment (FCUC) is proposed to address this challenge.
Image co-segmentation is an active computer vision task that aims to segment the common objects from a set of images.
Specifically, we consider the decentralized inverter-based secondary voltage control problem in distributed generators (DGs), which is first formulated as a cooperative multi-agent reinforcement learning (MARL) problem.
Traditional methods for solvability region analysis can only have inner approximations with inconclusive conservatism.
A modified link penalty method, which accounts for preference of using higher hierarchical roads, provides a route set with 97% coverage (80% overlap threshold).
Top performance in City-Scale Multi-Camera Vehicle Re-Identification demonstrated the advantage of our methods, and we got 5-th place in the vehicle Re-ID track of AIC2020.
Second, we provide a detailed discussion and overview of the technical characteristics of the different methods.
Recent progress in semantic segmentation is driven by deep Convolutional Neural Networks and large-scale labeled image datasets.
Ranked #13 on Few-Shot Semantic Segmentation on PASCAL-5i (1-Shot)
According to the results from our experiments, our CNN model is able to accurately estimate different people's gaze under various lighting conditions by different devices.
We conduct extensive experiments and demonstrate that our proposed approach is able to outperform the state-of-the-arts in terms of classification and label misalignment measures on three challenging datasets: Opportunity, Hand Gesture, and our new dataset.
Despite many advances made in the area, deformable targets and partial occlusions continue to represent key problems in visual tracking.