Papers
Thu 28 Oct 2021
189 papers
- Proximal Reinforcement Learning: Efficient Off-Policy Evaluation in Partially Observed Markov Decision ProcessesOffline RL and imitation learning from data → Offline RL algorithms
- Towards Model Agnostic Federated Learning Using Knowledge DistillationKnowledge distillation → Federated, robust and private distillation
- Learning Feasibility to Imitate Demonstrators with Different DynamicsOffline RL and imitation learning from data → Imitation learning methods
- Similarity-Aware Skill Reproduction based on Multi-Representational Learning from DemonstrationOffline RL and imitation learning from data → Robot learning from demonstration
- Human Activity Recognition using Attribute-Based Neural Networks and Context Information
- Generating synthetic transactional profiles
- HyperPINN: Learning parameterized differential equations with physics-informed hypernetworks
- Multi-Attribute Balanced Sampling for Disentangled GAN Controls
- Smart Fashion: A Review of AI Applications in the Fashion & Apparel Industry
- Towards a theory of quantum gravity from neural networks
- Click-Based Student Performance Prediction: A Clustering Guided Meta-Learning Approach
- Equivariant Contrastive Learning
- Fair Incentives for Repeated Engagement
- Tractability from overparametrization: The example of the negative perceptron
- Real-time multiview data fusion for object tracking with RGBD sensors
- A GIS Data Realistic Road Generation Approach for Traffic Simulation
- Two-sided fairness in rankings via Lorenz dominance
- NxMTransformer: Semi-Structured Sparsification for Natural Language Understanding via ADMM
- ICDM 2020 Knowledge Graph Contest: Consumer Event-Cause Extraction
- Open Problem: Tight Online Confidence Intervals for RKHS Elements
- FAST: DNN Training Under Variable Precision Block Floating Point with Stochastic Rounding
- VigDet: Knowledge Informed Neural Temporal Point Process for Coordination Detection on Social Media
- Using Text Analytics for Health to Get Meaningful Insights from a Corpus of COVID Scientific Papers
- Automated Translation of Rebar Information from GPR Data into As-Built BIM: A Deep Learning-based Approach
- On Wasted Contributions: Understanding the Dynamics of Contributor-Abandoned Pull Requests
- 10 Security and Privacy Problems in Large Foundation Models
- Scalable Unidirectional Pareto Optimality for Multi-Task Learning with Constraints
- HD-cos Networks: Efficient Neural Architectures for Secure Multi-Party Computation
- InfoGCL: Information-Aware Graph Contrastive Learning
- Universal Decision Models
- Improving Noise Robustness of Contrastive Speech Representation Learning with Speech Reconstruction
- RadBERT-CL: Factually-Aware Contrastive Learning For Radiology Report Classification
- Physics-Driven Learning of Wasserstein GAN for Density Reconstruction in Dynamic Tomography
- On the Use of CSI for the Generation of RF Fingerprints and Secret Keys
- Stochastic Mirror Descent: Convergence Analysis and Adaptive Variants via the Mirror Stochastic Polyak Stepsize
- What makes us curious? analysis of a corpus of open-domain questions
- Selective Regression Under Fairness Criteria
- A Computationally Efficient Method for Learning Exponential Family Distributions
- New SAR target recognition based on YOLO and very deep multi-canonical correlation analysis
- Neural Disparity Refinement for Arbitrary Resolution Stereo
- Accelerating Robotic Reinforcement Learning via Parameterized Action Primitives
- Dynamic Visual Reasoning by Learning Differentiable Physics Models from Video and Language
- Explaining Latent Representations with a Corpus of Examples
- MCUNetV2: Memory-Efficient Patch-based Inference for Tiny Deep Learning
- XDEEP-MSI: Explainable Bias-Rejecting Microsatellite Instability Deep Learning System In Colorectal Cancer
- Learning to Ground Multi-Agent Communication with Autoencoders
- Residual Relaxation for Multi-view Representation Learning
- Learning to Jump from Pixels
- Scatterbrain: Unifying Sparse and Low-rank Attention Approximation
- Bayesian Sequential Optimal Experimental Design for Nonlinear Models Using Policy Gradient Reinforcement Learning
- Wasserstein Distance Maximizing Intrinsic Control
- MEGAN: Memory Enhanced Graph Attention Network for Space-Time Video Super-Resolution
- Communication-Efficient ADMM-based Federated Learning
- Bridge the Gap Between CV and NLP! A Gradient-based Textual Adversarial Attack Framework
- On the Fairness of Machine-Assisted Human Decisions
- How to boost autoencoders?
- Cooperative Deep Q-learning Framework for Environments Providing Image Feedback
- Sobolev-type embeddings for neural network approximation spaces
- Class-wise Thresholding for Robust Out-of-Distribution Detection
- Learning to Control using Image Feedback
- Hyper-Representations: Self-Supervised Representation Learning on Neural Network Weights for Model Characteristic Prediction
- Decentralized Feature-Distributed Optimization for Generalized Linear Models
- OMASGAN: Out-of-Distribution Minimum Anomaly Score GAN for Sample Generation on the Boundary
- Cognitive network science quantifies feelings expressed in suicide letters and Reddit mental health communities
- UltraPose: Synthesizing Dense Pose with 1 Billion Points by Human-body Decoupling 3D Model
- Coresets for Time Series Clustering
- Self-Supervised Learning Disentangled Group Representation as Feature
- Understanding How Encoder-Decoder Architectures Attend
- Federated Learning with Heterogeneous Differential Privacy
- End-to-end Learning the Partial Permutation Matrix for Robust 3D Point Cloud Registration
- 'UFAL at MultiLexNorm 2021: Improving Multilingual Lexical Normalization by Fine-tuning ByT5
- From Machine Learning to Robotics: Challenges and Opportunities for Embodied Intelligence
- Multi-stage Clarification in Conversational AI: The case of Question-Answering Dialogue Systems
- Subpixel object segmentation using wavelets and multi resolution analysis
- Guided Evolution for Neural Architecture Search
- Exploring Covariate and Concept Shift for Detection and Calibration of Out-of-Distribution Data
- Pruning Attention Heads of Transformer Models Using A* Search: A Novel Approach to Compress Big NLP Architectures
- Conditional Inference and Activation of Knowledge Entities in ACT-R
- Re-calibrating Photometric Redshift Probability Distributions Using Feature-space Regression
- Generating 3D Molecules Conditional on Receptor Binding Sites with Deep Generative Models
- RGP: Neural Network Pruning through Its Regular Graph Structure
- URLB: Unsupervised Reinforcement Learning Benchmark
- The magnitude vector of images
- Dist2Cycle: A Simplicial Neural Network for Homology Localization
- BERTian Poetics: Constrained Composition with Masked LMs
- A Comparative Study of Coarse to Dense 3D Indoor Scene Registration Algorithms
- On Provable Benefits of Depth in Training Graph Convolutional Networks
- Conditioning Sparse Variational Gaussian Processes for Online Decision-making
- Privacy Aware Person Detection in Surveillance Data
- Labeled sample compression schemes for complexes of oriented matroids
- Extracting Expert's Goals by What-if Interpretable Modeling
- Authentication Attacks on Projection-based Cancelable Biometric Schemes
- Exoplanet atmosphere evolution: emulation with neural networks
- Blending Anti-Aliasing into Vision Transformer
- Diversity-Driven Combination for Grammatical Error Correction
- A first-order primal-dual method with adaptivity to local smoothness
- Deep Reinforcement Learning Aided Packet-Routing For Aeronautical Ad-Hoc Networks Formed by Passenger Planes
- Deep Learning Aided Packet Routing in Aeronautical Ad-Hoc Networks Relying on Real Flight Data: From Single-Objective to Near-Pareto Multi-Objective Optimization
- Deep Learning Analysis of Cardiac MRI in Legacy Datasets: Multi-Ethnic Study of Atherosclerosis
- Deep Learning Aided Routing for Space-Air-Ground Integrated Networks Relying on Real Satellite, Flight, and Shipping Data
All 189
- PAC-Bayesian Learning of Aggregated Binary Activated Neural Networks with Probabilities over Representations
- Aggregation as Unsupervised Learning and its Evaluation
- An Analysis of Programming Course Evaluations Before and After the Introduction of an Autograder
- Deep Calibration of Interest Rates Model
- Generating Table Vector Representations
- Confounds and Overestimations in Fake Review Detection: Experimentally Controlling for Product-Ownership and Data-Origin
- Contrast and Mix: Temporal Contrastive Video Domain Adaptation with Background Mixing
- Lightweight Mobile Automated Assistant-to-physician for Global Lower-resource Areas
- Multi-Class Anomaly Detection
- A Game-Theoretic Approach for Improving Generalization Ability of TSP Solvers
- Choosing the Best of Both Worlds: Diverse and Novel Recommendations through Multi-Objective Reinforcement Learning
- D2RLIR : an improved and diversified ranking function in interactive recommendation systems based on deep reinforcement learning
- MOOMIN: Deep Molecular Omics Network for Anti-Cancer Drug Combination Therapy
- Using Non-Linear Causal Models to Study Aerosol-Cloud Interactions in the Southeast Pacific
- SpineOne: A One-Stage Detection Framework for Degenerative Discs and Vertebrae
- Improving Causal Effect Estimation of Weighted RegressionBased Estimator using Neural Networks
- Meta Guided Metric Learner for Overcoming Class Confusion in Few-Shot Road Object Detection
- MMD Aggregated Two-Sample Test
- Leveraging Recursive Gumbel-Max Trick for Approximate Inference in Combinatorial Spaces
- Thermodynamics of Evolution and the Origin of Life
- LF-YOLO: A Lighter and Faster YOLO for Weld Defect Detection of X-ray Image
- Hindsight Goal Ranking on Replay Buffer for Sparse Reward Environment
- Learning Deep Representation with Energy-Based Self-Expressiveness for Subspace Clustering
- Orientation Probabilistic Movement Primitives on Riemannian Manifolds
- OneFlow: Redesign the Distributed Deep Learning Framework from Scratch
- Explicitly Modeling the Discriminability for Instance-Aware Visual Object Tracking
- Facial Emotion Recognition: A multi-task approach using deep learning
- Deformable Registration of Brain MR Images via a Hybrid Loss
- Empirical Analysis of Korean Public AI Hub Parallel Corpora and in-depth Analysis using LIWC
- Bridging Non Co-occurrence with Unlabeled In-the-wild Data for Incremental Object Detection
- Sliding Sequential CVAE with Time Variant Socially-aware Rethinking for Trajectory Prediction
- Deeptime: a Python library for machine learning dynamical models from time series data
- On the explainability of hospitalization prediction on a large COVID-19 patient dataset
- An Adaptable Approach to Learn Realistic Legged Locomotion without Examples
- Skeleton-Based Mutually Assisted Interacted Object Localization and Human Action Recognition
- Using Time-Series Privileged Information for Provably Efficient Learning of Prediction Models
- A machine learning approach for fighting the curse of dimensionality in global optimization
- Multivariate Empirical Mode Decomposition based Hybrid Model for Day-ahead Peak Load Forecasting
- DocScanner: Robust Document Image Rectification with Progressive Learning
- Gradient Inversion with Generative Image Prior
- Roto-translated Local Coordinate Frames For Interacting Dynamical Systems
- End-to-End Speech Emotion Recognition: Challenges of Real-Life Emergency Call Centers Data Recordings
- Multi-Task Neural Processes
- Probabilistic Autoencoder using Fisher Information
- Towards Large-Scale Rendering of Simulated Crops for Synthetic Ground Truth Generation on Modular Supercomputers
- Preventing posterior collapse in variational autoencoders for text generation via decoder regularization
- Dispensed Transformer Network for Unsupervised Domain Adaptation
- Semi-Siamese Bi-encoder Neural Ranking Model Using Lightweight Fine-Tuning
- A Novel Sample-efficient Deep Reinforcement Learning with Episodic Policy Transfer for PID-Based Control in Cardiac Catheterization Robots
- FocusFace: Multi-task Contrastive Learning for Masked Face Recognition
- Computational Intelligence and Deep Learning for Next-Generation Edge-Enabled Industrial IoT
- Exploration of Algorithmic Trading Strategies for the Bitcoin Market
- GPU based GMM segmentation of kinect data
- A recursive robust filtering approach for 3D registration
- Counterfactual Explanation of Brain Activity Classifiers using Image-to-Image Transfer by Generative Adversarial Network
- Modeling Heterogeneous Hierarchies with Relation-specific Hyperbolic Cones
- 3D Object Tracking with Transformer
- Efficient Meta Subspace Optimization
- Trading via Selective Classification
- Diagnosis of COVID-19 Using Machine Learning and Deep Learning: A review
- E-ffective: A Visual Analytic System for Exploring the Emotion and Effectiveness of Inspirational Speeches
- MERCURY: Accelerating DNN Training By Exploiting Input Similarity
- Degraded Reference Image Quality Assessment
- Pipeline Parallelism for Inference on Heterogeneous Edge Computing
- SMORE: Knowledge Graph Completion and Multi-hop Reasoning in Massive Knowledge Graphs
- Teaching an Active Learner with Contrastive Examples
- Colossal-AI: A Unified Deep Learning System For Large-Scale Parallel Training
- AEVA: Black-box Backdoor Detection Using Adversarial Extreme Value Analysis
- Sayer: Using Implicit Feedback to Optimize System Policies
- Generalized Depthwise-Separable Convolutions for Adversarially Robust and Efficient Neural Networks
- A Scenario-Based Platform for Testing Autonomous Vehicle Behavior Prediction Models in Simulation
- An Asymptotic Test for Conditional Independence using Analytic Kernel Embeddings
- Selective Sampling for Online Best-arm Identification
- Graph Communal Contrastive Learning
- Audio-visual Representation Learning for Anomaly Events Detection in Crowds
- Approximate Decomposable Submodular Function Minimization for Cardinality-Based Components
- An Operator Theoretic View on Pruning Deep Neural Networks
- CAP: Co-Adversarial Perturbation on Weights and Features for Improving Generalization of Graph Neural Networks
- RIM: Reliable Influence-based Active Learning on Graphs
- V2iFi: in-Vehicle Vital Sign Monitoring via Compact RF Sensing
- How Well Does Kohn-Sham Regularizer Work for Weakly Correlated Systems?
- From Intrinsic to Counterfactual: On the Explainability of Contextualized Recommender Systems
- A Sequence to Sequence Model for Extracting Multiple Product Name Entities from Dialog
- Hate Speech Classifiers Learn Human-Like Social Stereotypes
- SIM-ECG: A Signal Importance Mask-driven ECGClassification System
- ODMTCNet: An Interpretable Multi-view Deep Neural Network Architecture for Image Feature Representation
- Normality-Calibrated Autoencoder for Unsupervised Anomaly Detection on Data Contamination
- Characterizing and Taming Resolution in Convolutional Neural Networks
- Temporal-Difference Value Estimation via Uncertainty-Guided Soft Updates