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Found 15 papers, 4 papers with code
Contouring Error Bounded Control for Biaxial Switched Linear Systems
To address the need for improved contouring accuracy in industrial machines with position-dependent structural flexibility, this paper introduces a novel contouring error-bounded control algorithm for biaxial switched linear systems.
DA-STC: Domain Adaptive Video Semantic Segmentation via Spatio-Temporal Consistency
To solve the challenge, we propose a novel DA-STC method for domain adaptive video semantic segmentation, which incorporates a bidirectional multi-level spatio-temporal fusion module and a category-aware spatio-temporal feature alignment module to facilitate consistent learning for domain-invariant features.
Distributed Online Convex Optimization with Adversarial Constraints: Reduced Cumulative Constraint Violation Bounds under Slater's Condition
Moreover, if the loss functions are strongly convex, then the network regret bound is reduced to $\mathcal{O}(\log(T))$, and the network cumulative constraint violation bound is reduced to $\mathcal{O}(\sqrt{\log(T)T})$ and $\mathcal{O}(\log(T))$ without and with Slater's condition, respectively.
Data-Driven Inverse Reinforcement Learning for Expert-Learner Zero-Sum Games
In this paper, we formulate inverse reinforcement learning (IRL) as an expert-learner interaction whereby the optimal performance intent of an expert or target agent is unknown to a learner agent.
Safety-based Speed Control of a Wheelchair using Robust Adaptive Model Predictive Control
Electric-powered wheelchair plays an important role in providing accessibility for people with mobility impairment.
Geo-NI: Geometry-aware Neural Interpolation for Light Field Rendering
In this paper, we present a Geometry-aware Neural Interpolation (Geo-NI) framework for light field rendering.
Regret and Cumulative Constraint Violation Analysis for Online Convex Optimization with Long Term Constraints
A novel algorithm is first proposed and it achieves an $\mathcal{O}(T^{\max\{c, 1-c\}})$ bound for static regret and an $\mathcal{O}(T^{(1-c)/2})$ bound for cumulative constraint violation, where $c\in(0, 1)$ is a user-defined trade-off parameter, and thus has improved performance compared with existing results.
Regret and Cumulative Constraint Violation Analysis for Distributed Online Constrained Convex Optimization
This is a sequential decision making problem with two sequences of arbitrarily varying convex loss and constraint functions.
Revisiting Light Field Rendering with Deep Anti-Aliasing Neural Network
In this paper, we revisit the classic LF rendering framework to address both challenges by incorporating it with advanced deep learning techniques.
Light Field Reconstruction Using Convolutional Network on EPI and Extended Applications
The main problem in direct reconstruction on the EPI involves an information asymmetry between the spatial and angular dimensions, where the detailed portion in the angular dimensions is damaged by undersampling.
Incremental Data-driven Optimization of Complex Systems in Nonstationary Environments
Existing work on data-driven optimization focuses on problems in static environments, but little attention has been paid to problems in dynamic environments.
Spatial-Angular Attention Network for Light Field Reconstruction
In this paper, we propose a spatial-angular attention network to perceive correspondences in the light field non-locally, and reconstruction high angular resolution light field in an end-to-end manner.
A Primal-Dual SGD Algorithm for Distributed Nonconvex Optimization
The distributed nonconvex optimization problem of minimizing a global cost function formed by a sum of $n$ local cost functions by using local information exchange is considered.
Optimization and Control
LapEPI-Net: A Laplacian Pyramid EPI structure for Learning-based Dense Light Field Reconstruction
We then propose a novel network architecture for the LapEPI structure, termed as LapEPI-net.
Light Field Reconstruction Using Deep Convolutional Network on EPI
In this paper, we take advantage of the clear texture structure of the epipolar plane image (EPI) in the light field data and model the problem of light field reconstruction from a sparse set of views as a CNN-based angular detail restoration on EPI.
