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Found 24 papers, 4 papers with code
基于循环交互注意力网络的问答立场分析(A Recurrent Interactive Attention Network for Answer Stance Analysis)
针对问答立场任务中, 现有方法难以提取问答文本间的依赖关系问题, 本文提出一种基于循环交互注意力(Recurrent Interactive Attention, RIA)网络的问答立场分析方法。该方法通过模仿人类阅读理解时的思维方式, 基于交互注意力机制和循环迭代方法, 有效地从问题和答案的相互联系中挖掘问答文本的立场信息。此外, 该方法将问题进行陈述化表示, 有效地解决疑问句表述下问题文本无法明确表达自身立场的问题。实验结果表明, 本文方法取得了比现有模型方法更好的效果, 同时证明该方法能有效拟合问答立场分析任务中的问答对依赖关系。
Improving Empathetic Response Generation by Recognizing Emotion Cause in Conversations
The emotion cause is a stimulus for human emotions.
Agent-based Simulation for Online Mental Health Matching
Online mental health communities (OMHCs) are an effective and accessible channel to give and receive social support for individuals with mental and emotional issues.
Discrete Distribution Estimation under User-level Local Differential Privacy
Perhaps surprisingly, we show that in suitable parameter regimes, having $m$ samples per user is equivalent to having $m$ times more users, each with only one sample.
Learning For Predictive Control: A Dual Gaussian Process Approach
Gaussian process (GP) based estimation of system models is an effective tool to learn unknown dynamics directly from input/output data.
Learning Continuous Control Policies for Information-Theoretic Active Perception
This paper proposes a method for learning continuous control policies for active landmark localization and exploration using an information-theoretic cost.
TwiBot-22: Towards Graph-Based Twitter Bot Detection
Twitter bot detection has become an increasingly important task to combat misinformation, facilitate social media moderation, and preserve the integrity of the online discourse.
Histogram Estimation under User-level Privacy with Heterogeneous Data
We consider the heterogeneous scenario where both the quantity and distribution of data can be different for each user.
Human Behavior Recognition Method Based on CEEMD-ES Radar Selection
First, this method decomposes and reconstructs the radar signal according to the difference in the reflected echo frequency between the limbs and the trunk of the human body.
Empathetic Response Generation with State Management
The emotion-aware dialogue management contains two parts: (1) Emotion state tracking maintains the current emotion state of the user and (2) Empathetic dialogue policy selection predicts a target emotion and a user's intent based on the results of the emotion state tracking.
Learning Based Model Predictive Control for Quadcopters with Dual Gaussian Process
In this paper, we present a novel Dual Gaussian Process (DGP) based model predictive control strategy that improves the performance of a quadcopter during trajectory tracking.
Distributed Estimation with Multiple Samples per User: Sharp Rates and Phase Transition
We obtain tight minimax rates for the problem of distributed estimation of discrete distributions under communication constraints, where $n$ users observing $m $ samples each can broadcast only $\ell$ bits.
Performance, Successes and Limitations of Deep Learning Semantic Segmentation of Multiple Defects in Transmission Electron Micrographs
In this work, we perform semantic segmentation of multiple defect types in electron microscopy images of irradiated FeCrAl alloys using a deep learning Mask Regional Convolutional Neural Network (Mask R-CNN) model.
Multi defect detection and analysis of electron microscopy images with deep learning
Electron microscopy is widely used to explore defects in crystal structures, but human detecting of defects is often time-consuming, error-prone, and unreliable, and is not scalable to large numbers of images or real-time analysis.
OpenRooms: An Open Framework for Photorealistic Indoor Scene Datasets
Finally, we demonstrate that our framework may also be integrated with physics engines, to create virtual robotics environments with unique ground truth such as friction coefficients and correspondence to real scenes.
Textual Analysis of Communications in COVID-19 Infected Community on Social Media
During the COVID-19 pandemic, people started to discuss about pandemic-related topics on social media.
AutoFreeze: Automatically Freezing Model Blocks to Accelerate Fine-tuning
With the rapid adoption of machine learning (ML), a number of domains now use the approach of fine tuning models which were pre-trained on a large corpus of data.
Accelerating Deep Learning Inference via Learned Caches
We present the design of GATI, an end-to-end prediction serving system that incorporates learned caches for low-latency DNN inference.
Estimating Sparse Discrete Distributions Under Local Privacy and Communication Constraints
We consider the problem of estimating sparse discrete distributions under local differential privacy (LDP) and communication constraints.
Auto-calibration Method Using Stop Signs for Urban Autonomous Driving Applications
Calibration of sensors is fundamental to robust performance for intelligent vehicles.
Learning discrete distributions: user vs item-level privacy
If each user has $m$ samples, we show that straightforward applications of Laplace or Gaussian mechanisms require the number of users to be $\mathcal{O}(k/(m\alpha^2) + k/\epsilon\alpha)$ to achieve an $\ell_1$ distance of $\alpha$ between the true and estimated distributions, with the privacy-induced penalty $k/\epsilon\alpha$ independent of the number of samples per user $m$.
OpenRooms: An End-to-End Open Framework for Photorealistic Indoor Scene Datasets
Finally, we demonstrate that our framework may also be integrated with physics engines, to create virtual robotics environments with unique ground truth such as friction coefficients and correspondence to real scenes.
Tidal surface states as fingerprints of non-Hermitian nodal knot metals
Non-Hermitian nodal knot metals (NKMs) contains intricate complex-valued energy bands gives rise to knotted exceptional loops and new topological surface states.
Mesoscale and Nanoscale Physics Materials Science Other Condensed Matter Mathematical Physics Mathematical Physics Quantum Physics
Entanglement-guided architectures of machine learning by quantum tensor network
In this work, we implement simple numerical experiments, related to pattern/images classification, in which we represent the classifiers by many-qubit quantum states written in the matrix product states (MPS).
