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Found 18 papers, 1 papers with code
融合知识的多目标词联合框架语义分析模型(Knowledge-integrated Joint Model For Multi-target Frame Semantic Parsing)
“框架语义分析任务是自然语言处理领域的一项基础性任务。先前的研究工作大多针对单目标词进行模型设计, 无法一次性完成多个目标词的框架语义结构提取。本文提出了一个面向多目标的框架语义分析模型, 实现对多目标词的联合预测。该模型对框架语义分析的各项子任务进行交互性建模, 实现子任务间的双向交互。此外, 本文利用关系图网络对框架关系信息进行编码, 将其作为框架语义学知识融入模型中。实验表明, 本文模型在不借助额外语料的情况下相比之前模型都有不同程度的提高。消融实验证明了本文模型设计的有效性。此外我们分析了模型目前存在的局限性以及未来的改进方向。”
MemFusionMap: Working Memory Fusion for Online Vectorized HD Map Construction
We propose MemFusionMap, a novel temporal fusion model with enhanced temporal reasoning capabilities for online HD map construction.
CipherDM: Secure Three-Party Inference for Diffusion Model Sampling
Diffusion Models (DMs) achieve state-of-the-art synthesis results in image generation and have been applied to various fields.
Deception in Nash Equilibrium Seeking
Among the examples in the paper is a microeconomic duopoly in which the deceiver induces in the victim a belief that the buyers disfavor the deceiver more than they actually do, leading the victim to increase the price above the Nash price, and resulting in an increased profit for the deceiver and a decreased profit for the victim.
Strong anti-Hebbian plasticity alters the convexity of network attractor landscapes
We are specifically interested in how the attractor landscapes of such networks become altered as a function of the strength and nature (Hebbian vs. anti-Hebbian) of learning, which may have a bearing on the ability of such rules to mediate large-scale optimization problems.
SOM-Net: Unrolling the Subspace-based Optimization for Solving Full-wave Inverse Scattering Problems
The final output of the SOM-Net is the full predicted induced current, from which the scattered field and the permittivity image can also be deduced analytically.
A Double-Graph Based Framework for Frame Semantic Parsing
In this paper, we propose a Knowledge-guided Incremental semantic parser with Double-graph (KID).
A Fast Alternating Minimization Algorithm for Coded Aperture Snapshot Spectral Imaging Based on Sparsity and Deep Image Priors
Coded aperture snapshot spectral imaging (CASSI) is a technique used to reconstruct three-dimensional hyperspectral images (HSIs) from one or several two-dimensional projection measurements.
A Stochastic Binary Vertex-Triggering Resetting Algorithm for Global Synchronization of Pulse-Coupled Oscillators
Toward the end of the paper, we present numerical demonstrations for the validity of the result and, also, numerical studies about the times needed to reach synchronization for various information flow topologies.
Deep Probabilistic Time Series Forecasting using Augmented Recurrent Input for Dynamic Systems
Thereafter, we first investigate the methodological characteristics of the proposed deep probabilistic sequence model on toy cases, and then comprehensively demonstrate the superiority of our model against existing deep probabilistic SSM models through extensive numerical experiments on eight system identification benchmarks from various dynamic systems.
A Dataset and Benchmark Towards Multi-Modal Face Anti-Spoofing Under Surveillance Scenarios
Besides, we propose an Attention based Face Anti-spoofing network with Feature Augment (AFA) to solve the FAS towards low-quality face images.
Gossip over Holonomic Graphs
A gossip process is an iterative process in a multi-agent system where only two neighboring agents communicate at each iteration and update their states.
Optimization and Control
Sparse Linear Ensemble Systems and Structural Controllability
A sparsity pattern is structurally controllable if it admits a controllable linear ensemble system.
Controllability Issues of Linear Ensemble Systems over Multi-dimensional Parameterization Spaces
We address an open problem in ensemble control: Whether there exist controllable linear ensemble systems over multi-dimensional parameterization spaces?
Passive TCP Identification for Wired and WirelessNetworks: A Long-Short Term Memory Approach
TCP congestion control algorithm identification (TCP identification) can be used to significantly improve network efficiency.
Global Synchronization of Clocks in Directed Rooted Acyclic Graphs: A Hybrid Systems Approach
In this paper, we study the problem of robust global synchronization of resetting clocks in multi-agent networked systems, where by robust global synchronization we mean synchronization that is insensitive to arbitrarily small disturbances, and which is achieved from all initial conditions.
Systems and Control
Rotated Feature Network for multi-orientation object detection
General detectors follow the pipeline that feature maps extracted from ConvNets are shared between classification and regression tasks.
