Papers
Fri 1 Oct 2021
168 papers
- How To Not Drive: Learning Driving Constraints from DemonstrationEnd-to-end autonomous driving → Imitation-learning end-to-end planners
- Motion Planning for Autonomous Vehicles in the Presence of Uncertainty Using Reinforcement LearningEnd-to-end autonomous driving → Reinforcement learning for driving
- Score-Based Generative ClassifiersDiffusion models → Diffusion foundations and sampling
- Learning from Demonstrations for Autonomous Soft-tissue RetractionOffline RL and imitation learning from data → Safe offline RL
- Student Helping Teacher: Teacher Evolution via Self-Knowledge DistillationKnowledge distillation → General knowledge distillation methods
- Offline Reinforcement Learning with Reverse Model-based ImaginationOffline RL and imitation learning from data → Offline RL algorithms
- Neural sentence embedding models for semantic similarity estimation in the biomedical domain
- Natural Computational Architectures for Cognitive Info-Communication
- One Timestep is All You Need: Training Spiking Neural Networks with Ultra Low Latency
- Surrogate-Based Black-Box Optimization Method for Costly Molecular Properties
- Cluster Analysis on Jester Dataset: A Review
- SOUL: An Energy-Efficient Unsupervised Online Learning Seizure Detection Classifier
- Prediction of Energy Consumption for Variable Customer Portfolios Including Aleatoric Uncertainty Estimation
- OPAD: An Optimized Policy-based Active Learning Framework for Document Content Analysis
- Breast Cancer Diagnosis in Two-View Mammography Using End-to-End Trained EfficientNet-Based Convolutional Network
- CCS-GAN: COVID-19 CT-scan classification with very few positive training images
- Implementation of Parallel Simplified Swarm Optimization in CUDA
- Extended dynamic mode decomposition with dictionary learning using neural ordinary differential equations
- Artificial Neural Network and its Application Research Progress in Distillation
- Real-Time Predictive Maintenance using Autoencoder Reconstruction and Anomaly Detection
- Label Propagation Through Optimal Transport
- Robust and Decomposable Average Precision for Image Retrieval
- A review of Generative Adversarial Networks (GANs) and its applications in a wide variety of disciplines -- From Medical to Remote Sensing
- Machine Learning with Knowledge Constraints for Process Optimization of Open-Air Perovskite Solar Cell Manufacturing
- Simulated annealing for optimization of graphs and sequences
- Investigating Robustness of Dialog Models to Popular Figurative Language Constructs
- Fast Multi-Resolution Transformer Fine-tuning for Extreme Multi-label Text Classification
- Learning Compact Representations of Neural Networks using DiscriminAtive Masking (DAM)
- Learning through atypical "phase transitions" in overparameterized neural networks
- Multi-view SA-LA Net: A framework for simultaneous segmentation of RV on multi-view cardiac MR Images
- A systematic evaluation of methods for cell phenotype classification using single-cell RNA sequencing data
- Speech Technology for Everyone: Automatic Speech Recognition for Non-Native English with Transfer Learning
- Contraction Theory for Nonlinear Stability Analysis and Learning-based Control: A Tutorial Overview
- Multi-Agent Algorithmic Recourse
- Low Frequency Names Exhibit Bias and Overfitting in Contextualizing Language Models
- Automatic Home-based Screening of Obstructive Sleep Apnea Using Single Channel Electrocardiogram and SPO2 Signals
- Sparse Deep Learning: A New Framework Immune to Local Traps and Miscalibration
- Multi-lane Cruising Using Hierarchical Planning and Reinforcement Learning
- RoomStructNet: Learning to Rank Non-Cuboidal Room Layouts From Single View
- Batch size-invariance for policy optimization
- ML4C: Seeing Causality Through Latent Vicinity
- ALBU: An approximate Loopy Belief message passing algorithm for LDA to improve performance on small data sets
- Factored couplings in multi-marginal optimal transport via difference of convex programming
- On the complexity of the optimal transport problem with graph-structured cost
- Accelerate Distributed Stochastic Descent for Nonconvex Optimization with Momentum
- Calibrated Adversarial Training
- Self-Attentive Constituency Parsing for UCCA-based Semantic Parsing
- SPEC: Seeing People in the Wild with an Estimated Camera
- Predicting erectile dysfunction after treatment for localized prostate cancer
- Expected Validation Performance and Estimation of a Random Variable's Maximum
- Delayed rejection Hamiltonian Monte Carlo for sampling multiscale distributions
- Inexact bilevel stochastic gradient methods for constrained and unconstrained lower-level problems
- Algorithm Fairness in AI for Medicine and Healthcare
- Reconstructing group wavelet transform from feature maps with a reproducing kernel iteration
- STRONG: Synchronous and asynchronous RObust Network localization, under Non-Gaussian noise
- Sentiment and structure in word co-occurrence networks on Twitter
- Classification of Time-Series Data Using Boosted Decision Trees
- SMATE: Semi-Supervised Spatio-Temporal Representation Learning on Multivariate Time Series
- Reconstruction for Powerful Graph Representations
- Conditional Deep Gaussian Processes: empirical Bayes hyperdata learning
- Weight Vector Tuning and Asymptotic Analysis of Binary Linear Classifiers
- Improving Punctuation Restoration for Speech Transcripts via External Data
- Natural language understanding for logical games
- Stochastic Contrastive Learning
- Video Temporal Relationship Mining for Data-Efficient Person Re-identification
- Self-Supervised Decomposition, Disentanglement and Prediction of Video Sequences while Interpreting Dynamics: A Koopman Perspective
- Discovery of interpretable structural model errors by combining Bayesian sparse regression and data assimilation: A chaotic Kuramoto-Sivashinsky test case
- Self-supervised Secondary Landmark Detection via 3D Representation Learning
- Applying Differential Privacy to Tensor Completion
- Evaluating the fairness of fine-tuning strategies in self-supervised learning
- A Cram'er Distance perspective on Quantile Regression based Distributional Reinforcement Learning
- TEACh: Task-driven Embodied Agents that Chat
- Layer-wise and Dimension-wise Locally Adaptive Federated Learning
- A survey on active noise control techniques -- Part I: Linear systems
- A survey on datasets for fairness-aware machine learning
- Unsupervised Motion Representation Learning with Capsule Autoencoders
- Do Self-Supervised and Supervised Methods Learn Similar Visual Representations?
- Consistent Explanations by Contrastive Learning
- Mask or Non-Mask? Robust Face Mask Detector via Triplet-Consistency Representation Learning
- Unpacking the Interdependent Systems of Discrimination: Ableist Bias in NLP Systems through an Intersectional Lens
- Calibrating Concepts and Operations: Towards Symbolic Reasoning on Real Images
- LEMON: Explainable Entity Matching
- Belief propagation for permutations, rankings, and partial orders
- Optic Disc Segmentation using Disk-Centered Patch Augmentation
- ASH: A Modern Framework for Parallel Spatial Hashing in 3D Perception
- An Ensemble-based Multi-Criteria Decision Making Method for COVID-19 Cough Classification
- Predicting Consumer Purchasing Decision in The Online Food Delivery Industry
- Probabilistic Robust Autoencoders for Outlier Detection
- Preconditioned Plug-and-Play ADMM with Locally Adjustable Denoiser for Image Restoration
- Personalized Rehabilitation Robotics based on Online Learning Control
- Robustly Removing Deep Sea Lighting Effects for Visual Mapping of Abyssal Plains
- Learning to Ask for Data-Efficient Event Argument Extraction
- SECDA: Efficient Hardware/Software Co-Design of FPGA-based DNN Accelerators for Edge Inference
- ResNet strikes back: An improved training procedure in timm
- Survey and synthesis of state of the art in driver monitoring
- Instance Segmentation Challenge Track Technical Report, VIPriors Workshop at ICCV 2021: Task-Specific Copy-Paste Data Augmentation Method for Instance Segmentation
- New Evolutionary Computation Models and their Applications to Machine Learning
- Dimension Reduction for Fr'echet Regression
- A Graph-theoretic Algorithm for Small Bowel Path Tracking in CT Scans
- MonoCInIS: Camera Independent Monocular 3D Object Detection using Instance Segmentation
All 168
- Characterizing Concurrency Mechanisms for NVIDIA GPUs under Deep Learning Workloads
- Towards Gradient-based Bilevel Optimization with Non-convex Followers and Beyond
- Phonology Recognition in American Sign Language
- SAM: A Self-adaptive Attention Module for Context-Aware Recommendation System
- Arbitrary Marginal Neural Ratio Estimation for Simulation-based Inference
- Sim and Real: Better Together
- Guiding Evolutionary Strategies by Differentiable Robot Simulators
- Towards Protecting Face Embeddings in Mobile Face Verification Scenarios
- Topologically-Informed Atlas Learning
- Predicting Flat-Fading Channels via Meta-Learned Closed-Form Linear Filters and Equilibrium Propagation
- Learning of Inter-Label Geometric Relationships Using Self-Supervised Learning: Application To Gleason Grade Segmentation
- Cellular traffic offloading via Opportunistic Networking with Reinforcement Learning
- Personalized Retrogress-Resilient Framework for Real-World Medical Federated Learning
- Tree in Tree: from Decision Trees to Decision Graphs
- Online Primal-Dual Algorithms with Predictions for Packing Problems
- GAN-based Reactive Motion Synthesis with Class-aware Discriminators for Human-human Interaction
- Smooth Normalizing Flows
- Summarize and Search: Learning Consensus-aware Dynamic Convolution for Co-Saliency Detection
- PhiNets: a scalable backbone for low-power AI at the edge
- Geometry Attention Transformer with Position-aware LSTMs for Image Captioning
- State-Space Models Win the IEEE DataPort Competition on Post-covid Day-ahead Electricity Load Forecasting
- Discovering Boundary Values of Feature-based Machine Learning Classifiers through Exploratory Datamorphic Testing
- Visual Cluster Separation Using High-Dimensional Sharpened Dimensionality Reduction
- DCT based Fusion of Variable Exposure Images for HDRI
- Leveraging power grid topology in machine learning assisted optimal power flow
- Divergence-Regularized Multi-Agent Actor-Critic
- Powerpropagation: A sparsity inducing weight reparameterisation
- Learning Reward Functions from Scale Feedback
- Generalizable Human Pose Triangulation
- TyXe: Pyro-based Bayesian neural nets for Pytorch
- From SLAM to Situational Awareness: Challenges and Survey
- Learn to Communicate with Neural Calibration: Scalability and Generalization
- A Survey of Knowledge Enhanced Pre-trained Models
- Inductive Representation Learning in Temporal Networks via Mining Neighborhood and Community Influences
- Generative Memory-Guided Semantic Reasoning Model for Image Inpainting
- Rapid Assessments of Light-Duty Gasoline Vehicle Emissions Using On-Road Remote Sensing and Machine Learning
- The Complexity of Learning Approval-Based Multiwinner Voting Rules
- Open-set Classification of Common Waveforms Using A Deep Feed-forward Network and Binary Isolation Forest Models
- Synergizing between Self-Training and Adversarial Learning for Domain Adaptive Object Detection
- Learner to learner fuzzy profiles similarity using a hybrid interaction analysis grid
- Lightweight Transformer in Federated Setting for Human Activity Recognition
- 3rd Place Scheme on Instance Segmentation Track of ICCV 2021 VIPriors Challenges
- Improving Object Permanence using Agent Actions and Reasoning
- On the Importance of Gradients for Detecting Distributional Shifts in the Wild
- Beyond Neighbourhood-Preserving Transformations for Quantization-Based Unsupervised Hashing
- Spiking Hyperdimensional Network: Neuromorphic Models Integrated with Memory-Inspired Framework
- Inverse airfoil design method for generating varieties of smooth airfoils using conditional WGAN-gp
- DNN-Opt: An RL Inspired Optimization for Analog Circuit Sizing using Deep Neural Networks
- Unsupervised Belief Representation Learning with Information-Theoretic Variational Graph Auto-Encoders
- Q-Net: A Quantitative Susceptibility Mapping-based Deep Neural Network for Differential Diagnosis of Brain Iron Deposition in Hemochromatosis
- Batched Thompson Sampling
- Error-free approximation of explicit linear MPC through lattice piecewise affine expression
- Perturbated Gradients Updating within Unit Space for Deep Learning
- Predicting COVID-19 Patient Shielding: A Comprehensive Study
- Improving Load Forecast in Energy Markets During COVID-19
- DualNet: Continual Learning, Fast and Slow
- Empirical Quantitative Analysis of COVID-19 Forecasting Models
- BERT4GCN: Using BERT Intermediate Layers to Augment GCN for Aspect-based Sentiment Classification
- Machine learning models for prediction of droplet collision outcomes
- Large-scale ASR Domain Adaptation using Self- and Semi-supervised Learning
- Building an Efficient and Effective Retrieval-based Dialogue System via Mutual Learning
- Asymptotic Performance of Thompson Sampling in the Batched Multi-Armed Bandits
- Under the Microscope: Interpreting Readability Assessment Models for Filipino
- Span Labeling Approach for Vietnamese and Chinese Word Segmentation
- Incremental Layer-wise Self-Supervised Learning for Efficient Speech Domain Adaptation On Device
- Lagrangian Inference for Ranking Problems
- Iterative Teacher-Aware Learning
- UserIdentifier: Implicit User Representations for Simple and Effective Personalized Sentiment Analysis