Papers
Wed 10 Feb 2021
156 papers
- Personalization for Web-based Services using Offline Reinforcement LearningOffline RL and imitation learning from data → Offline RL algorithms
- Meta Federated LearningLLM safety and security → Federated unlearning and poisoning
- Learning Equational Theorem ProvingOffline RL and imitation learning from data → Imitation learning methods
- Argmax Flows and Multinomial Diffusion: Learning Categorical DistributionsDiffusion models → Medical imaging and segmentation
- Risk-Averse Offline Reinforcement LearningOffline RL and imitation learning from data → Offline RL algorithms
- Robust Federated Learning with Attack-Adaptive AggregationLLM safety and security → Federated unlearning and poisoning
- Deep Reinforcement Learning with Symmetric Prior for Predictive Power Allocation to Mobile Users
- Privacy-Preserving Graph Convolutional Networks for Text Classification
- Learning Skill Equivalencies Across Platform Taxonomies
- Signal Propagation in a Gradient-Based and Evolutionary Learning System
- Multi-Agent Multi-Armed Bandits with Limited Communication
- Generating 3D structures from a 2D slice with GAN-based dimensionality expansion
- Accelerating COVID-19 research with graph mining and transformer-based learning
- Computationally Efficient Multiscale Neural Networks Applied To Fluid Flow In Complex 3D Porous Media
- Comparison of Machine Learning Classifiers to Predict Patient Survival and Genetics of GBM: Towards a Standardized Model for Clinical Implementation
- Leveraging Reinforcement Learning for evaluating Robustness of KNN Search Algorithms
- Artificial Intelligence based Autonomous Molecular Design for Medical Therapeutic: A Perspective
- Modeling the Interaction between Agents in Cooperative Multi-Agent Reinforcement Learning
- An Ensemble Deep Convolutional Neural Network Model for Electricity Theft Detection in Smart Grids
- Feature Analyses and Modelling of Lithium-ion Batteries Manufacturing based on Random Forest Classification
- Defense Against Reward Poisoning Attacks in Reinforcement Learning
- AdaFuse: Adaptive Temporal Fusion Network for Efficient Action Recognition
- Deep Variational Autoencoder with Shallow Parallel Path for Top-N Recommendation (VASP)
- Predicting Customer Lifetime Values -- ecommerce use case
- Fused Acoustic and Text Encoding for Multimodal Bilingual Pretraining and Speech Translation
- Early Performance Prediction using Interpretable Patterns in Programming Process Data
- Risk-Averse Bayes-Adaptive Reinforcement Learning
- Customizing Contextualized Language Models forLegal Document Reviews
- Artificial intelligence in communication impacts language and social relationships
- Development of Crop Yield Estimation Model using Soil and Environmental Parameters
- Self-Supervised VQ-VAE for One-Shot Music Style Transfer
- Faster Maximum Feasible Subsystem Solutions for Dense Constraint Matrices
- Temporal Parallelization of Inference in Hidden Markov Models
- Self-supervised learning for fast and scalable time series hyper-parameter tuning
- Refinement of polygonal grids using Convolutional Neural Networks with applications to polygonal Discontinuous Galerkin and Virtual Element methods
- Emojis predict dropouts of remote workers: An empirical study of emoji usage on GitHub
- Sequential change-point detection for mutually exciting point processes over networks
- Differentiable Generative Phonology
- Sparse-Push: Communication- & Energy-Efficient Decentralized Distributed Learning over Directed & Time-Varying Graphs with non-IID Datasets
- Domain Adaptation In Reinforcement Learning Via Latent Unified State Representation
- SCA-Net: A Self-Correcting Two-Layer Autoencoder for Hyper-spectral Unmixing
- Derivative-Free Reinforcement Learning: A Review
- A Topological Approach for Motion Track Discrimination
- UAV Localization Using Autoencoded Satellite Images
- Novel Techniques to Assess Predictive Systems and Reduce Their Alarm Burden
- Real-Time Likelihood-Free Inference of Roman Binary Microlensing Events with Amortized Neural Posterior Estimation
- Scale Normalized Image Pyramids with AutoFocus for Object Detection
- Automated Video Labelling: Identifying Faces by Corroborative Evidence
- Training Vision Transformers for Image Retrieval
- An Exact Solver for the Weston-Watkins SVM Subproblem
- Energy-Harvesting Distributed Machine Learning
- Generating Synthetic Text Data to Evaluate Causal Inference Methods
- Voice Cloning: a Multi-Speaker Text-to-Speech Synthesis Approach based on Transfer Learning
- Agnostic Proper Learning of Halfspaces under Gaussian Marginals
- On the Regularity of Attention
- NAST: Non-Autoregressive Spatial-Temporal Transformer for Time Series Forecasting
- Addressing the Topological Defects of Disentanglement via Distributed Operators
- Searching for Fast Model Families on Datacenter Accelerators
- Exploiting Depth Information for Wildlife Monitoring
- Systematic Generalization in Neural Networks-based Multivariate Time Series Forecasting Models
- DANTE: Predicting Insider Threat using LSTM on system logs
- Improving Model-Based Reinforcement Learning with Internal State Representations through Self-Supervision
- Fast Classification Learning with Neural Networks and Conceptors for Speech Recognition and Car Driving Maneuvers
- Classification of Long Noncoding RNA Elements Using Deep Convolutional Neural Networks and Siamese Networks
- A Witness Two-Sample Test
- TINKER: A framework for Open source Cyberthreat Intelligence
- Hyperbolic Generative Adversarial Network
- Partial transfusion: on the expressive influence of trainable batch norm parameters for transfer learning
- On the Existence of Optimal Transport Gradient for Learning Generative Models
- Slicing the hypercube is not easy
- Deep learning approaches to surrogates for solving the diffusion equation for mechanistic real-world simulations
- Dynamic β-VAEs for quantifying biodiversity by clustering optically recorded insect signals
- Detecting corruption in single-bidder auctions via positive-unlabelled learning
- Robustness in Compressed Neural Networks for Object Detection
- On Disentanglement in Gaussian Process Variational Autoencoders
- A Similarity-preserving Neural Network Trained on Transformed Images Recapitulates Salient Features of the Fly Motion Detection Circuit
- On the Suboptimality of Thompson Sampling in High Dimensions
- A Neural Network with Local Learning Rules for Minor Subspace Analysis
- Dysplasia grading of colorectal polyps through CNN analysis of WSI
- Towards More Fine-grained and Reliable NLP Performance Prediction
- On the Properties of Kullback-Leibler Divergence Between Multivariate Gaussian Distributions
- Adversarial Robustness: What fools you makes you stronger
- Multi-turn Dialogue Reading Comprehension with Pivot Turns and Knowledge
- Robust estimation of tree structured models
- The human-AI relationship in decision-making: AI explanation to support people on justifying their decisions
- Two Novel Performance Improvements for Evolving CNN Topologies
- Reference-based Texture transfer for Single Image Super-resolution of Magnetic Resonance images
- Adaptive Processor Frequency Adjustment for Mobile Edge Computing with Intermittent Energy Supply
- Searching for Alignment in Face Recognition
- A Framework of Inertial Alternating Direction Method of Multipliers for Non-Convex Non-Smooth Optimization
- Dompteur: Taming Audio Adversarial Examples
- Node-Level Membership Inference Attacks Against Graph Neural Networks
- MAIN: Multihead-Attention Imputation Networks
- BRECQ: Pushing the Limit of Post-Training Quantization by Block Reconstruction
- Doctor Imitator: Hand-Radiography-based Bone Age Assessment by Imitating Scoring Methods
- Learning to Enhance Visual Quality via Hyperspectral Domain Mapping
- NUVA: A Naming Utterance Verifier for Aphasia Treatment
- Non-stationary Reinforcement Learning without Prior Knowledge: An Optimal Black-box Approach
- Application of Yolo on Mask Detection Task
- Enhancing efficiency of object recognition in different categorization levels by reinforcement learning in modular spiking neural networks
All 156
- Improving Aerial Instance Segmentation in the Dark with Self-Supervised Low Light Enhancement
- Learning Interaction-Aware Trajectory Predictions for Decentralized Multi-Robot Motion Planning in Dynamic Environments
- Strength of Minibatch Noise in SGD
- GuiltyWalker: Distance to illicit nodes in the Bitcoin network
- RoBIC: A benchmark suite for assessing classifiers robustness
- Towards Certifying L-infinity Robustness using Neural Networks with L-inf-dist Neurons
- Regional Attention with Architecture-Rebuilt 3D Network for RGB-D Gesture Recognition
- From Sampling to Optimization on Discrete Domains with Applications to Determinant Maximization
- The Hessigheim 3D (H3D) Benchmark on Semantic Segmentation of High-Resolution 3D Point Clouds and Textured Meshes from UAV LiDAR and Multi-View-Stereo
- On PyTorch Implementation of Density Estimators for von Mises-Fisher and Its Mixture
- Understanding Instance-Level Label Noise: Disparate Impacts and Treatments
- Enhancing Real-World Adversarial Patches through 3D Modeling of Complex Target Scenes
- Language Models for Lexical Inference in Context
- An Adaptive Stochastic Sequential Quadratic Programming with Differentiable Exact Augmented Lagrangians
- Time series forecasting from partial observations via Non-negative Matrix Factorization
- Conditional Loss and Deep Euler Scheme for Time Series Generation
- Improved Algorithms for Efficient Active Learning Halfspaces with Massart and Tsybakov noise
- CIFS: Improving Adversarial Robustness of CNNs via Channel-wise Importance-based Feature Selection
- Explaining Inference Queries with Bayesian Optimization
- Searching CUDA code autotuning spaces with hardware performance counters: data from benchmarks running on various GPU architectures
- Inductive Granger Causal Modeling for Multivariate Time Series
- Using hardware performance counters to speed up autotuning convergence on GPUs
- An Efficient Pessimistic-Optimistic Algorithm for Stochastic Linear Bandits with General Constraints
- Clusterability as an Alternative to Anchor Points When Learning with Noisy Labels
- Bayesian Inference with Certifiable Adversarial Robustness
- Finding the Stochastic Shortest Path with Low Regret: The Adversarial Cost and Unknown Transition Case
- Biomedical Question Answering: A Survey of Approaches and Challenges
- A Generic Object Re-identification System for Short Videos
- Stability of SGD: Tightness Analysis and Improved Bounds
- Hybrid In-memory Computing Architecture for the Training of Deep Neural Networks
- Reinforcement Learning for Optimized Beam Training in Multi-Hop Terahertz Communications
- Player Modeling via Multi-Armed Bandits
- Regression Oracles and Exploration Strategies for Short-Horizon Multi-Armed Bandits
- Input Similarity from the Neural Network Perspective
- Simple Agent, Complex Environment: Efficient Reinforcement Learning with Agent States
- SensPick: Sense Picking for Word Sense Disambiguation
- Locally Free Weight Sharing for Network Width Search
- Policy Augmentation: An Exploration Strategy for Faster Convergence of Deep Reinforcement Learning Algorithms
- Memory-Associated Differential Learning
- Patterns, predictions, and actions: A story about machine learning
- Detecting Localized Adversarial Examples: A Generic Approach using Critical Region Analysis
- Advanced Ore Mine Optimisation under Uncertainty Using Evolution
- Driver2vec: Driver Identification from Automotive Data
- Culture-inspired Multi-modal Color Palette Generation and Colorization: A Chinese Youth Subculture Case
- Sequential vessel segmentation via deep channel attention network
- Towards Better Explanations of Class Activation Mapping
- Early Abandoning and Pruning for Elastic Distances including Dynamic Time Warping
- FLOP: Federated Learning on Medical Datasets using Partial Networks
- VINS: Visual Search for Mobile User Interface Design
- Task-Optimal Exploration in Linear Dynamical Systems
- Polarimetric Monocular Dense Mapping Using Relative Deep Depth Prior
- D2A U-Net: Automatic Segmentation of COVID-19 Lesions from CT Slices with Dilated Convolution and Dual Attention Mechanism
- Attentive Gaussian processes for probabilistic time-series generation
- Statistical Inference for Polyak-Ruppert Averaged Zeroth-order Stochastic Gradient Algorithm
- Boosting Template-based SSVEP Decoding by Cross-domain Transfer Learning
- Last Query Transformer RNN for knowledge tracing