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Understanding the Effect of Out-of-distribution Examples and Interactive Explanations on Human-AI Decision Making
Although AI holds promise for improving human decision making in societa...
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Morphology Matters: A Multilingual Language Modeling Analysis
Prior studies in multilingual language modeling (e.g., Cotterell et al.,...
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Uncertainty Estimation in Medical Image Localization: Towards Robust Anterior Thalamus Targeting for Deep Brain Stimulation
Atlas-based methods are the standard approaches for automatic targeting ...
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Label-Wise Document Pre-Training for Multi-Label Text Classification
A major challenge of multi-label text classification (MLTC) is to stimul...
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The flare Package for High Dimensional Linear Regression and Precision Matrix Estimation in R
This paper describes an R package named flare, which implements a family...
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The huge Package for High-dimensional Undirected Graph Estimation in R
We describe an R package named huge which provides easy-to-use functions...
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Few-shot Slot Tagging with Collapsed Dependency Transfer and Label-enhanced Task-adaptive Projection Network
In this paper, we explore the slot tagging with only a few labeled suppo...
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A Deep Learning based Wearable Healthcare IoT Device for AI-enabled Hearing Assistance Automation
With the recent booming of artificial intelligence (AI), particularly de...
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Neural Polysynthetic Language Modelling
Research in natural language processing commonly assumes that approaches...
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EQL – an extremely easy to learn knowledge graph query language, achieving highspeed and precise search
EQL, also named as Extremely Simple Query Language, can be widely used i...
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"Why is 'Chicago' deceptive?" Towards Building Model-Driven Tutorials for Humans
To support human decision making with machine learning models, we often ...
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AdvCodec: Towards A Unified Framework for Adversarial Text Generation
While there has been great interest in generating imperceptible adversar...
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Automatic quality assessment for 2D fetal sonographic standard plane based on multi-task learning
The quality control of fetal sonographic (FS) images is essential for th...
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Clustering Uncertain Data via Representative Possible Worlds with Consistency Learning
Clustering uncertain data is an essential task in data mining for the in...
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Attributed Graph Learning with 2-D Graph Convolution
Graph convolutional neural networks have demonstrated promising performa...
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MVDLite: A Light-weight Model View Definition Representation with Fast Validation for Building Information Model
Model View Definition (MVD) is the standard methodology to define the ex...
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MVDLite: A Light-weight Representation of Model View Definition with Fast Validation for BIM Applications
Model View Definition (MVD) is the standard methodology to define the pa...
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Fast Low-rank Metric Learning for Large-scale and High-dimensional Data
Low-rank metric learning aims to learn better discrimination of data sub...
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More Supervision, Less Computation: Statistical-Computational Tradeoffs in Weakly Supervised Learning
We consider the weakly supervised binary classification problem where th...
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Few-Shot Sequence Labeling with Label Dependency Transfer
Few-shot sequence labeling faces a unique challenge compared with the ot...
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Attributed Graph Clustering via Adaptive Graph Convolution
Attributed graph clustering is challenging as it requires joint modellin...
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Estimating and Inferring the Maximum Degree of Stimulus-Locked Time-Varying Brain Connectivity Networks
Neuroscientists have enjoyed much success in understanding brain functio...
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Covariance-based sample selection for heterogenous data: Applications to gene expression and autism risk gene detection
Risk for autism can be influenced by genetic mutations in hundreds of ge...
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Finite-Sample Analyses for Fully Decentralized Multi-Agent Reinforcement Learning
Despite the increasing interest in multi-agent reinforcement learning (M...
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EASYFLOW: Keep Ethereum Away From Overflow
While Ethereum smart contracts enabled a wide range of blockchain applic...
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Performance assessment of the deep learning technologies in grading glaucoma severity
Objective: To validate and compare the performance of eight available de...
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SDFN: Segmentation-based Deep Fusion Network for Thoracic Disease Classification in Chest X-ray Images
This study aims to automatically diagnose thoracic diseases depicted on ...
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Super-pixel cloud detection using Hierarchical Fusion CNN
Cloud detection plays a very important role in the process of remote sen...
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Parametrized Deep Q-Networks Learning: Reinforcement Learning with Discrete-Continuous Hybrid Action Space
Most existing deep reinforcement learning (DRL) frameworks consider eith...
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Fully Implicit Online Learning
Regularized online learning is widely used in machine learning. In this ...
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High Temperature Structure Detection in Ferromagnets
This paper studies structure detection problems in high temperature ferr...
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TStarBots: Defeating the Cheating Level Builtin AI in StarCraft II in the Full Game
Starcraft II (SCII) is widely considered as the most challenging Real Ti...
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A convex formulation for high-dimensional sparse sliced inverse regression
Sliced inverse regression is a popular tool for sufficient dimension red...
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Factorized Q-Learning for Large-Scale Multi-Agent Systems
Deep Q-learning has achieved a significant success in single-agent decis...
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Diffusion Approximations for Online Principal Component Estimation and Global Convergence
In this paper, we propose to adopt the diffusion approximation tools to ...
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Online ICA: Understanding Global Dynamics of Nonconvex Optimization via Diffusion Processes
Solving statistical learning problems often involves nonconvex optimizat...
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Curse of Heterogeneity: Computational Barriers in Sparse Mixture Models and Phase Retrieval
We study the fundamental tradeoffs between statistical accuracy and comp...
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A Unified Framework for Testing High Dimensional Parameters: A Data-Adaptive Approach
High dimensional hypothesis test deals with models in which the number o...
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Marginal Policy Gradients for Complex Control
Many complex domains, such as robotics control and real-time strategy (R...
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Efficient, Certifiably Optimal High-Dimensional Clustering
We consider SDP relaxation methods for data and variable clustering prob...
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Feedback-Based Tree Search for Reinforcement Learning
Inspired by recent successes of Monte-Carlo tree search (MCTS) in a numb...
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Discrete Factorization Machines for Fast Feature-based Recommendation
User and item features of side information are crucial for accurate reco...
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Fully Decentralized Multi-Agent Reinforcement Learning with Networked Agents
We consider the problem of fully decentralized multi-agent reinforcement...
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The Enemy Among Us: Detecting Hate Speech with Threats Based 'Othering' Language Embeddings
Offensive or antagonistic language targeted at individuals and social gr...
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Cyber Hate Classification: 'Othering' Language And Paragraph Embedding
Hateful and offensive language (also known as hate speech or cyber hate)...
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A New Perspective on Robust M-Estimation: Finite Sample Theory and Applications to Dependence-Adjusted Multiple Testing
Heavy-tailed errors impair the accuracy of the least squares estimate, w...
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On Stein's Identity and Near-Optimal Estimation in High-dimensional Index Models
We consider estimating the parametric components of semi-parametric mult...
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Inter-Subject Analysis: Inferring Sparse Interactions with Dense Intra-Graphs
We develop a new modeling framework for Inter-Subject Analysis (ISA). Th...
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Property Testing in High Dimensional Ising models
This paper explores the information-theoretic limitations of graph prope...
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Adaptive Inferential Method for Monotone Graph Invariants
We consider the problem of undirected graphical model inference. In many...
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