Papers
Tue 8 Jun 2021
240 papers
- Curriculum Design for Teaching via Demonstrations: Theory and ApplicationsOffline RL and imitation learning from data → Inverse reinforcement learning
- Don't Get Yourself into Trouble! Risk-aware Decision-Making for Autonomous VehiclesEnd-to-end autonomous driving → Reinforcement learning for driving
- BERT Learns to Teach: Knowledge Distillation with Meta LearningKnowledge distillation → General knowledge distillation methods
- Adaptive Machine UnlearningLLM safety and security → Machine unlearning
- Exploration and preference satisfaction trade-off in reward-free learningLLM alignment / RLHF / preference optimisation → Reward modeling and RLHF
- Learning by Distillation: A Self-Supervised Learning Framework for Optical Flow EstimationKnowledge distillation → Detection and dense prediction distillation
- Provable Guarantees for Self-Supervised Deep Learning with Spectral Contrastive LossMechanistic interpretability → Sparse autoencoder training and evaluation
- Automatic 2D-3D Registration without Contrast Agent during Neurovascular Interventions
- Deep Random Projection Outlyingness for Unsupervised Anomaly Detection
- Artificial Intelligence in Minimally Invasive Interventional Treatment
- Classification of Contract-Amendment Relationships
- Surrogate-based variational data assimilation for tidal modelling
- Understanding top-down attention using task-oriented ablation design
- Detecting chaos in lineage-trees: A deep learning approach
- Learning Full Configuration Interaction Electron Correlations with Deep Learning
- GeoMol: Torsional Geometric Generation of Molecular 3D Conformer Ensembles
- Non-Autoregressive Electron Redistribution Modeling for Reaction Prediction
- Machine Learning Based Prediction of Future Stress Events in a Driving Scenario
- An Online Riemannian PCA for Stochastic Canonical Correlation Analysis
- Investigating sanity checks for saliency maps with image and text classification
- Predicting the Popularity of Reddit Posts with AI
- Recurrent Inference Machines as inverse problem solvers for MR relaxometry
- Recommending Multiple Criteria Decision Analysis Methods with A New Taxonomy-based Decision Support System
- Learning Functional Priors and Posteriors from Data and Physics
- A Bagging and Boosting Based Convexly Combined Optimum Mixture Probabilistic Model
- Multi-hop Graph Convolutional Network with High-order Chebyshev Approximation for Text Reasoning
- Marginalizable Density Models
- Learning subtree pattern importance for Weisfeiler-Lehmanbased graph kernels
- AdaMatch: A Unified Approach to Semi-Supervised Learning and Domain Adaptation
- A Markov Decision Process Approach for Managing Medical Drone Deliveries
- ParChain: A Framework for Parallel Hierarchical Agglomerative Clustering using Nearest-Neighbor Chain
- Tiplines to Combat Misinformation on Encrypted Platforms: A Case Study of the 2019 Indian Election on WhatsApp
- OODIn: An Optimised On-Device Inference Framework for Heterogeneous Mobile Devices
- FastSeq: Make Sequence Generation Faster
- Labeled Data Generation with Inexact Supervision
- Measurable Monte Carlo Search Error Bounds
- NRGNN: Learning a Label Noise-Resistant Graph Neural Network on Sparsely and Noisily Labeled Graphs
- Boolean Matrix Factorization via Nonnegative Auxiliary Optimization
- Job Dispatching Policies for Queueing Systems with Unknown Service Rates
- Scale Free Adversarial Multi Armed Bandits
- On the Evolution of Neuron Communities in a Deep Learning Architecture
- Provably Faster Algorithms for Bilevel Optimization
- Handcrafted Backdoors in Deep Neural Networks
- Learning to Price Against a Moving Target
- Explainable AI for medical imaging: Explaining pneumothorax diagnoses with Bayesian Teaching
- Bayesian Optimization over Hybrid Spaces
- Dynamic Instance-Wise Classification in Correlated Feature Spaces
- Sequential End-to-End Intent and Slot Label Classification and Localization
- Comprehension Based Question Answering using Bloom's Taxonomy
- TED-net: Convolution-free T2T Vision Transformer-based Encoder-decoder Dilation network for Low-dose CT Denoising
- Compacter: Efficient Low-Rank Hypercomplex Adapter Layers
- Predicting the Success of Domain Adaptation in Text Similarity
- Automatically Differentiable Random Coefficient Logistic Demand Estimation
- VALUE: A Multi-Task Benchmark for Video-and-Language Understanding Evaluation
- On the Lack of Robust Interpretability of Neural Text Classifiers
- PAM: Understanding Product Images in Cross Product Category Attribute Extraction
- Densely connected normalizing flows
- SpeechBrain: A General-Purpose Speech Toolkit
- Self-Supervised Learning with Data Augmentations Provably Isolates Content from Style
- EXPObench: Benchmarking Surrogate-based Optimisation Algorithms on Expensive Black-box Functions
- Vector Quantized Models for Planning
- Neural Extractive Search
- Check It Again: Progressive Visual Question Answering via Visual Entailment
- PEARL: Data Synthesis via Private Embeddings and Adversarial Reconstruction Learning
- TIMEDIAL: Temporal Commonsense Reasoning in Dialog
- Simulated Adversarial Testing of Face Recognition Models
- Data-Efficient Instance Generation from Instance Discrimination
- Translate, then Parse! A strong baseline for Cross-Lingual AMR Parsing
- Are Pretrained Transformers Robust in Intent Classification? A Missing Ingredient in Evaluation of Out-of-Scope Intent Detection
- XtremeDistilTransformers: Task Transfer for Task-agnostic Distillation
- Safe Deep Q-Network for Autonomous Vehicles at Unsignalized Intersection
- Scaling Vision Transformers
- Turing: an Accurate and Interpretable Multi-Hypothesis Cross-Domain Natural Language Database Interface
- Hierarchical Lov'asz Embeddings for Proposal-free Panoptic Segmentation
- A Survey of Transformers
- DETReg: Unsupervised Pretraining with Region Priors for Object Detection
- Automatic Generation of Machine Learning Synthetic Data Using ROS
- LEADS: Learning Dynamical Systems that Generalize Across Environments
- Object Based Attention Through Internal Gating
- What Makes Multi-modal Learning Better than Single (Provably)
- Can You Learn an Algorithm? Generalizing from Easy to Hard Problems with Recurrent Networks
- Chasing Sparsity in Vision Transformers: An End-to-End Exploration
- RobustNav: Towards Benchmarking Robustness in Embodied Navigation
- Learning from Multiple Noisy Partial Labelers
- LaplaceNet: A Hybrid Graph-Energy Neural Network for Deep Semi-Supervised Classification
- A critical look at the current train/test split in machine learning
- MVT: Mask Vision Transformer for Facial Expression Recognition in the wild
- Cyberbullying Detection Using Deep Neural Network from Social Media Comments in Bangla Language
- Federated Hyperparameter Tuning: Challenges, Baselines, and Connections to Weight-Sharing
- Towards Practical Credit Assignment for Deep Reinforcement Learning
- Towards a Theoretical Framework of Out-of-Distribution Generalization
- A Deep Value-network Based Approach for Multi-Driver Order Dispatching
- Description and Discussion on DCASE 2021 Challenge Task 2: Unsupervised Anomalous Sound Detection for Machine Condition Monitoring under Domain Shifted Conditions
- Parameter-efficient Multi-task Fine-tuning for Transformers via Shared Hypernetworks
- Low-Rank Subspaces in GANs
- The Fast Kernel Transform
- Sketch-Based Anomaly Detection in Streaming Graphs
- Are VQA Systems RAD? Measuring Robustness to Augmented Data with Focused Interventions
- There Is No Turning Back: A Self-Supervised Approach for Reversibility-Aware Reinforcement Learning
- MoCo-Flow: Neural Motion Consensus Flow for Dynamic Humans in Stationary Monocular Cameras
All 240
- One Semantic Parser to Parse Them All: Sequence to Sequence Multi-Task Learning on Semantic Parsing Datasets
- Interpreting Deep Learning based Cerebral Palsy Prediction with Channel Attention
- Lower Bounds and Optimal Algorithms for Smooth and Strongly Convex Decentralized Optimization Over Time-Varying Networks
- Detecting Anomalous Event Sequences with Temporal Point Processes
- Augmenting Molecular Deep Generative Models with Topological Data Analysis Representations
- A multi-centre polyp detection and segmentation dataset for generalisability assessment
- Muddling Label Regularization: Deep Learning for Tabular Datasets
- North Carolina COVID-19 Agent-Based Model Framework for Hospitalization Forecasting Overview, Design Concepts, and Details Protocol
- Adaptive transfer learning
- Reading StackOverflow Encourages Cheating: Adding Question Text Improves Extractive Code Generation
- Robust Generalization despite Distribution Shift via Minimum Discriminating Information
- CLTR: An End-to-End, Transformer-Based System for Cell Level Table Retrieval and Table Question Answering
- Adversarial Training for Machine Reading Comprehension with Virtual Embeddings
- Enhancing Robustness of Neural Networks through Fourier Stabilization
- SDGMNet: Statistic-based Dynamic Gradient Modulation for Local Descriptor Learning
- On the relation between statistical learning and perceptual distances
- Hash Layers For Large Sparse Models
- Back2Future: Leveraging Backfill Dynamics for Improving Real-time Predictions in Future
- Context-Specific Causal Discovery for Categorical Data Using Staged Trees
- SynthRef: Generation of Synthetic Referring Expressions for Object Segmentation
- CSRNet: Cascaded Selective Resolution Network for Real-time Semantic Segmentation
- Flow Network based Generative Models for Non-Iterative Diverse Candidate Generation
- Learning compositional structures for semantic graph parsing
- Property-Aware Robot Object Manipulation: a Generative Approach
- FL-Market: Trading Private Models in Federated Learning
- Using a New Nonlinear Gradient Method for Solving Large Scale Convex Optimization Problems with an Application on Arabic Medical Text
- Learning Markov State Abstractions for Deep Reinforcement Learning
- Segmentation and ABCD rule extraction for skin tumors classification
- Nonsmooth Implicit Differentiation for Machine Learning and Optimization
- Efficient Online Learning for Dynamic k-Clustering
- Reinforced Few-Shot Acquisition Function Learning for Bayesian Optimization
- Progressive Spatio-Temporal Bilinear Network with Monte Carlo Dropout for Landmark-based Facial Expression Recognition with Uncertainty Estimation
- Weighted Sparse Subspace Representation: A Unified Framework for Subspace Clustering, Constrained Clustering, and Active Learning
- Contrastive Representation Learning for Hand Shape Estimation
- Breaking the Limits of Message Passing Graph Neural Networks
- Learning Riemannian Manifolds for Geodesic Motion Skills
- Hyperbolic Temporal Knowledge Graph Embeddings with Relational and Time Curvatures
- Residual Feedback Learning for Contact-Rich Manipulation Tasks with Uncertainty
- Obtaining Better Static Word Embeddings Using Contextual Embedding Models
- A Unified Generative Framework for Aspect-Based Sentiment Analysis
- Unsupervised Word Segmentation from Discrete Speech Units in Low-Resource Settings
- Principled Hyperedge Prediction with Structural Spectral Features and Neural Networks
- NWT: Towards natural audio-to-video generation with representation learning
- Generative adversarial network with object detector discriminator for enhanced defect detection on ultrasonic B-scans
- Staircase Attention for Recurrent Processing of Sequences
- Raw Waveform Encoder with Multi-Scale Globally Attentive Locally Recurrent Networks for End-to-End Speech Recognition
- 3D Human Pose Estimation Based on 2D-3D Consistency with Synchronized Adversarial Training
- Inference for Network Regression Models with Community Structure
- HPRNet: Hierarchical Point Regression for Whole-Body Human Pose Estimation
- Supervised Machine Learning with Plausible Deniability
- On the Connection between Local Attention and Dynamic Depth-wise Convolution
- Question Generation for Adaptive Education
- Provably Robust Detection of Out-of-distribution Data (almost) for free
- Interpretable agent communication from scratch (with a generic visual processor emerging on the side)
- Coresets for Classification -- Simplified and Strengthened
- Meta-Learning to Compositionally Generalize
- Parameter Inference with Bifurcation Diagrams
- The Medkit-Learn(ing) Environment: Medical Decision Modelling through Simulation
- Definitions of intent suitable for algorithms
- Towards interval uncertainty propagation control in bivariate aggregation processes and the introduction of width-limited interval-valued overlap functions
- Giving Commands to a Self-Driving Car: How to Deal with Uncertain Situations?
- BIGDML: Towards Exact Machine Learning Force Fields for Materials
- Decentralized Learning in Online Queuing Systems
- On the role of feedback in visual processing: a predictive coding perspective
- A Falta de Pan, Buenas Son Tortas: The Efficacy of Predicted UPOS Tags for Low Resource UD Parsing
- Multi-output Gaussian Processes for Uncertainty-aware Recommender Systems
- Time-series Imputation of Temporally-occluded Multiagent Trajectories
- Dynamic Sparse Training for Deep Reinforcement Learning
- A Modest Pareto Optimisation Analysis of Dependency Parsers in 2021
- On the use of automatically generated synthetic image datasets for benchmarking face recognition
- Defining definition: a Text mining Approach to Define Innovative Technological Fields
- MindReader: Recommendation over Knowledge Graph Entities with Explicit User Ratings
- Grapevine Winter Pruning Automation: On Potential Pruning Points Detection through 2D Plant Modeling using Grapevine Segmentation
- Cooperative Stochastic Multi-agent Multi-armed Bandits Robust to Adversarial Corruptions
- Efficient Sampling in POMDPs with Lipschitz Bandits for Motion Planning in Continuous Spaces
- Seismic Inverse Modeling Method based on Generative Adversarial Network
- Targeted Active Learning for Bayesian Decision-Making
- Realistic Evaluation Principles for Cross-document Coreference Resolution
- Stability and Generalization of Bilevel Programming in Hyperparameter Optimization
- What training reveals about neural network complexity
- LipSync3D: Data-Efficient Learning of Personalized 3D Talking Faces from Video using Pose and Lighting Normalization
- The Randomness of Input Data Spaces is an A Priori Predictor for Generalization
- Image2Point: 3D Point-Cloud Understanding with 2D Image Pretrained Models
- White Paper Assistance: A Step Forward Beyond the Shortcut Learning
- Highly accurate digital traffic recording as a basis for future mobility research: Methods and concepts of the research project HDV-Mess
- Interpretable and Low-Resource Entity Matching via Decoupling Feature Learning from Decision Making
- Scalable conditional deep inverse Rosenblatt transports using tensor-trains and gradient-based dimension reduction
- On Improving Adversarial Transferability of Vision Transformers
- Incorporating NODE with Pre-trained Neural Differential Operator for Learning Dynamics
- Neural Hybrid Automata: Learning Dynamics with Multiple Modes and Stochastic Transitions
- Fast Federated Learning in the Presence of Arbitrary Device Unavailability
- PlayVirtual: Augmenting Cycle-Consistent Virtual Trajectories for Reinforcement Learning
- Cross-Domain Gradient Discrepancy Minimization for Unsupervised Domain Adaptation
- Few-Shot Action Localization without Knowing Boundaries
- To Smooth or Not? When Label Smoothing Meets Noisy Labels
- RECOWNs: Probabilistic Circuits for Trustworthy Time Series Forecasting
- Risk Ranked Recall: Collision Safety Metric for Object Detection Systems in Autonomous Vehicles
- Unbalanced Optimal Transport through Non-negative Penalized Linear Regression
- Adversarial Semantic Hallucination for Domain Generalized Semantic Segmentation
- Broadcasted Residual Learning for Efficient Keyword Spotting
- Image Deformation Estimation via Multi-Objective Optimization
- Cheap and Good? Simple and Effective Data Augmentation for Low Resource Machine Reading
- Efficient Speech Emotion Recognition Using Multi-Scale CNN and Attention
- EnMcGAN: Adversarial Ensemble Learning for 3D Complete Renal Structures Segmentation
- Conversational Fashion Image Retrieval via Multiturn Natural Language Feedback
- Left Ventricle Contouring in Cardiac Images Based on Deep Reinforcement Learning
- Multi-dataset Pretraining: A Unified Model for Semantic Segmentation
- The best of both worlds: stochastic and adversarial episodic MDPs with unknown transition
- Theoretically Motivated Data Augmentation and Regularization for Portfolio Construction
- Self-supervised Graph-level Representation Learning with Local and Global Structure
- Harnessing Unrecognizable Faces for Improving Face Recognition
- A self consistent theory of Gaussian Processes captures feature learning effects in finite CNNs
- Fully Transformer Networks for Semantic Image Segmentation
- Design of Low-Artifact Interpolation Kernels by Means of Computer Algebra
- Swords: A Benchmark for Lexical Substitution with Improved Data Coverage and Quality
- Ultra-Fine Entity Typing with Weak Supervision from a Masked Language Model
- Linear Convergence of Entropy-Regularized Natural Policy Gradient with Linear Function Approximation
- Diverse Part Discovery: Occluded Person Re-identification with Part-Aware Transformer
- Variational AutoEncoder for Reference based Image Super-Resolution
- A Lightweight and Gradient-Stable Neural Layer
- Insight from NLP Analysis: COVID-19 Vaccines Sentiments on Social Media
- RewardsOfSum: Exploring Reinforcement Learning Rewards for Summarisation
- Multi-Agent Cooperative Bidding Games for Multi-Objective Optimization in e-Commercial Sponsored Search
- Salvage of Supervision in Weakly Supervised Object Detection
- Coarse-to-Fine Curriculum Learning
- LocalTrans: A Multiscale Local Transformer Network for Cross-Resolution Homography Estimation
- Semantically Adversarial Scenario Generation with Explicit Knowledge Guidance
- Self-supervised and Supervised Joint Training for Resource-rich Machine Translation
- Affinity Attention Graph Neural Network for Weakly Supervised Semantic Segmentation
- Discriminative Triad Matching and Reconstruction for Weakly Referring Expression Grounding
- Graph-MLP: Node Classification without Message Passing in Graph
- GSGP-CUDA -- a CUDA framework for Geometric Semantic Genetic Programming
- Sample Complexity of Tree Search Configuration: Cutting Planes and Beyond
- Deep Learning Statistical Arbitrage
- Subject-Independent Brain-Computer Interface for Decoding High-Level Visual Imagery Tasks
- SpaceMeshLab: Spatial Context Memoization and Meshgrid Atrous Convolution Consensus for Semantic Segmentation
- Manifold Topology Divergence: a Framework for Comparing Data Manifolds
- Hybrid Method Based on NARX models and Machine Learning for Pattern Recognition
- Intrinsic Dimension Estimation Using Wasserstein Distances
- Disfl-QA: A Benchmark Dataset for Understanding Disfluencies in Question Answering