Papers
Mon 22 Feb 2021
163 papers
- Uncertainty Estimation Using Riemannian Model Dynamics for Offline Reinforcement LearningOffline RL and imitation learning from data → Offline RL algorithms
- Multi-View Feature Representation for Dialogue Generation with Bidirectional DistillationKnowledge distillation → Multimodal distillation
- Provably Improved Context-Based Offline Meta-RL with Attention and Contrastive LearningOffline RL and imitation learning from data → Decision transformers and sequence modeling
- MobILE: Model-Based Imitation Learning From Observation AloneOffline RL and imitation learning from data → Imitation learning methods
- Computationally Efficient Learning of Statistical Manifolds
- A Fast Heuristic for Gateway Location in Wireless Backhaul of 5G Ultra-Dense Networks
- Believe The HiPe: Hierarchical Perturbation for Fast, Robust, and Model-Agnostic Saliency Mapping
- A Novel Framework for Neural Architecture Search in the Hill Climbing Domain
- Variable Weights Neural Network For Diabetes Classification
- KAM Theory Meets Statistical Learning Theory: Hamiltonian Neural Networks with Non-Zero Training Loss
- Parallelizing Legendre Memory Unit Training
- On Feature Collapse and Deep Kernel Learning for Single Forward Pass Uncertainty
- Exploring Supervised and Unsupervised Rewards in Machine Translation
- MixUp Training Leads to Reduced Overfitting and Improved Calibration for the Transformer Architecture
- Home and destination attachment: study of cultural integration on Twitter
- Learning Low-dimensional Manifolds for Scoring of Tissue Microarray Images
- Procam Calibration from a Single Pose of a Planar Target
- Explore the Context: Optimal Data Collection for Context-Conditional Dynamics Models
- No-Reference Quality Assessment for 360-degree Images by Analysis of Multi-frequency Information and Local-global Naturalness
- MagNet: A Neural Network for Directed Graphs
- Approximate Knowledge Graph Query Answering: From Ranking to Binary Classification
- Exploiting Multimodal Reinforcement Learning for Simultaneous Machine Translation
- Direct-Search for a Class of Stochastic Min-Max Problems
- Lightweight Combinational Machine Learning Algorithm for Sorting Canine Torso Radiographs
- Sandwich Batch Normalization: A Drop-In Replacement for Feature Distribution Heterogeneity
- FaCells. Teaching Machines the Language of Lines: Per Point Attribute Scores for Face-Sketch Classification
- Shadow Image Enlargement Distortion Removal
- Individualized Context-Aware Tensor Factorization for Online Games Predictions
- Generative Archimedean Copulas
- HALMA: Humanlike Abstraction Learning Meets Affordance in Rapid Problem Solving
- Understanding Catastrophic Forgetting and Remembering in Continual Learning with Optimal Relevance Mapping
- Action Redundancy in Reinforcement Learning
- Stratified Experience Replay: Correcting Multiplicity Bias in Off-Policy Reinforcement Learning
- Distributed Application of Guideline-Based Decision Support through Mobile Devices: Implementation and Evaluation
- You Only Compress Once: Optimal Data Compression for Estimating Linear Models
- Ps and Qs: Quantization-aware pruning for efficient low latency neural network inference
- RUBERT: A Bilingual Roman Urdu BERT Using Cross Lingual Transfer Learning
- Sustainable Federated Learning
- On Interaction Between Augmentations and Corruptions in Natural Corruption Robustness
- Reinforcement Learning with Prototypical Representations
- Softmax Policy Gradient Methods Can Take Exponential Time to Converge
- Interpret-able feedback for AutoML systems
- Automated Evaluation Of Psychotherapy Skills Using Speech And Language Technologies
- Style and Pose Control for Image Synthesis of Humans from a Single Monocular View
- Adversarial Shape Learning for Building Extraction in VHR Remote Sensing Images
- Cognitively Aided Zero-Shot Automatic Essay Grading
- Modeling Multi-Destination Trips with Sketch-Based Model
- Gaussian Process Nowcasting: Application to COVID-19 Mortality Reporting
- Image Captioning using Deep Stacked LSTMs, Contextual Word Embeddings and Data Augmentation
- Uncertainty Maximization in Partially Observable Domains: A Cognitive Perspective
- Subspace-Based Feature Fusion From Hyperspectral And Multispectral Image For Land Cover Classification
- Neural Pharmacodynamic State Space Modeling
- Non-Convex Optimization with Spectral Radius Regularization
- Learning Contact Dynamics using Physically Structured Neural Networks
- A Theory of Label Propagation for Subpopulation Shift
- Quantitative photoacoustic oximetry imaging by multiple illumination learned spectral decoloring
- Variational Data Assimilation with a Learned Inverse Observation Operator
- Sign-regularized Multi-task Learning
- Deep Reinforcement Learning for Dynamic Spectrum Sharing of LTE and NR
- Linear Transformers Are Secretly Fast Weight Programmers
- Few-shot Network Anomaly Detection via Cross-network Meta-learning
- Generator Surgery for Compressed Sensing
- Federated f-Differential Privacy
- Creating a Universal Dependencies Treebank of Spoken Frisian-Dutch Code-switched Data
- Phase Space Reconstruction Network for Lane Intrusion Action Recognition
- Domain Adaptation in Dialogue Systems using Transfer and Meta-Learning
- Program Synthesis Guided Reinforcement Learning for Partially Observed Environments
- Wider Vision: Enriching Convolutional Neural Networks via Alignment to External Knowledge Bases
- Deepfake Video Detection Using Convolutional Vision Transformer
- Reinforcement Learning of the Prediction Horizon in Model Predictive Control
- Direct Estimation of Appearance Models for Segmentation
- Adversarial robust weighted Huber regression
- Probing Multimodal Embeddings for Linguistic Properties: the Visual-Semantic Case
- Generating Human Readable Transcript for Automatic Speech Recognition with Pre-trained Language Model
- Towards Causal Representation Learning
- REMOD: Relation Extraction for Modeling Online Discourse
- User Factor Adaptation for User Embedding via Multitask Learning
- RCoNet: Deformable Mutual Information Maximization and High-order Uncertainty-aware Learning for Robust COVID-19 Detection
- Position Information in Transformers: An Overview
- Improving Lossless Compression Rates via Monte Carlo Bits-Back Coding
- Comparative Fault Location Estimation by Using Image Processing in Mixed Transmission Lines
- Nonparametric adaptive active learning under local smoothness condition
- Kernel Ridge Riesz Representers: Generalization, Mis-specification, and the Counterfactual Effective Dimension
- SENTINEL: Taming Uncertainty with Ensemble-based Distributional Reinforcement Learning
- Determination of Fault Location in Transmission Lines with Image Processing and Artificial Neural Networks
- On the Effects of Quantisation on Model Uncertainty in Bayesian Neural Networks
- Anyone GAN Sing
- Hierarchical Graph Representations in Digital Pathology
- Escaping from Zero Gradient: Revisiting Action-Constrained Reinforcement Learning via Frank-Wolfe Policy Optimization
- Improved Learning of Robot Manipulation Tasks via Tactile Intrinsic Motivation
- How are journals cited? characterizing journal citations by type of citation
- The Uncanny Similarity of Recurrence and Depth
- Resilience of Bayesian Layer-Wise Explanations under Adversarial Attacks
- The Moral Foundations of Left-Wing Authoritarianism: On the Character, Cohesion, and Clout of Tribal Equalitarian Discourse
- LogME: Practical Assessment of Pre-trained Models for Transfer Learning
- Software Architecture for Next-Generation AI Planning Systems
- Kindergarden quantum mechanics graduates (...or how I learned to stop gluing LEGO together and love the ZX-calculus)
- Better Call the Plumber: Orchestrating Dynamic Information Extraction Pipelines
- Adaptive Multi-View ICA: Estimation of noise levels for optimal inference
- Entities of Interest
All 163
- Return-Based Contrastive Representation Learning for Reinforcement Learning
- Bilingual Language Modeling, A transfer learning technique for Roman Urdu
- Co-occurrences using Fasttext embeddings for word similarity tasks in Urdu
- Few Shot Learning for Information Verification
- Learning Purified Feature Representations from Task-irrelevant Labels
- A Relational Tsetlin Machine with Applications to Natural Language Understanding
- Explainers in the Wild: Making Surrogate Explainers Robust to Distortions through Perception
- Shapley values for feature selection: The good, the bad, and the axioms
- Semantically Meaningful Class Prototype Learning for One-Shot Image Semantic Segmentation
- Using Prior Knowledge to Guide BERT's Attention in Semantic Textual Matching Tasks
- Deep Learning for Robust Motion Segmentation with Non-Static Cameras
- Escaping Poor Local Minima in Large Scale Robust Estimation
- Approximation of dilation-based spatial relations to add structural constraints in neural networks
- Interpretative Computer-aided Lung Cancer Diagnosis: from Radiology Analysis to Malignancy Evaluation
- Joint Intent Detection And Slot Filling Based on Continual Learning Model
- Revisiting Classification Perspective on Scene Text Recognition
- Conditional Positional Encodings for Vision Transformers
- A Probabilistically Motivated Learning Rate Adaptation for Stochastic Optimization
- On the robustness of randomized classifiers to adversarial examples
- Non-linear, Sparse Dimensionality Reduction via Path Lasso Penalized Autoencoders
- Linear unit-tests for invariance discovery
- Handling Epistemic and Aleatory Uncertainties in Probabilistic Circuits
- Subword Pooling Makes a Difference
- Learning atrial fiber orientations and conductivity tensors from intracardiac maps using physics-informed neural networks
- Multiple Kernel-Based Online Federated Learning
- Recursive Least Squares Based Refinement Network for the Rollout Trajectory Prediction Methods
- Contour Loss for Instance Segmentation via k-step Distance Transformation Image
- Evaluating Contextualized Language Models for Hungarian
- Expanding boundaries of Gap Safe screening
- BayesPerf: Minimizing Performance Monitoring Errors Using Bayesian Statistics
- LightCAKE: A Lightweight Framework for Context-Aware Knowledge Graph Embedding
- SALT: A Semi-automatic Labeling Tool for RGB-D Video Sequences
- Local Calibration: Metrics and Recalibration
- Provably Correct Training of Neural Network Controllers Using Reachability Analysis
- Improving Uncertainty Calibration via Prior Augmented Data
- PrivateMail: Supervised Manifold Learning of Deep Features With Differential Privacy for Image Retrieval
- Neural Delay Differential Equations
- Characterizing and Optimizing EDA Flows for the Cloud
- Clustering Algorithm to Detect Adversaries in Federated Learning
- Person Re-identification based on Robust Features in Open-world
- Decoupled and Memory-Reinforced Networks: Towards Effective Feature Learning for One-Step Person Search
- ReINTEL Challenge 2020: Exploiting Transfer Learning Models for Reliable Intelligence Identification on Vietnamese Social Network Sites
- Attention Models for Point Clouds in Deep Learning: A Survey
- Residual-Aided End-to-End Learning of Communication System without Known Channel
- NTopo: Mesh-free Topology Optimization using Implicit Neural Representations
- PCB-Fire: Automated Classification and Fault Detection in PCB
- Weighted Graph Nodes Clustering via Gumbel Softmax
- Slowly Varying Regression under Sparsity
- UniT: Multimodal Multitask Learning with a Unified Transformer
- Divide-and-conquer methods for big data analysis
- Post-hoc Overall Survival Time Prediction from Brain MRI
- Unsupervised Meta Learning for One Shot Title Compression in Voice Commerce
- Hide and Seek: Outwitting Community Detection Algorithms
- Self-Supervised Learning of Graph Neural Networks: A Unified Review
- Coping with Mistreatment in Fair Algorithms
- CSIT-Free Model Aggregation for Federated Edge Learning via Reconfigurable Intelligent Surface
- MetaDelta: A Meta-Learning System for Few-shot Image Classification
- Communication Efficient Parallel Reinforcement Learning
- Dissecting the Diffusion Process in Linear Graph Convolutional Networks
- Provable Super-Convergence with a Large Cyclical Learning Rate
- Dither computing: a hybrid deterministic-stochastic computing framework
- Three dimensional unique identifier based automated georeferencing and coregistration of point clouds in underground environment
- Abstraction and Analogy-Making in Artificial Intelligence