yusuke1997/dblp-id-title huggingface dataset:
Mem-Rec: Memory Efficient Recommendation System using Alternative Representation
A Single-Stage Multi-Style License Plate Recognition Method Based on Attention
Deep-n-Cheap: An Automated Search Framework for Low Complexity Deep Learning
Cautious Actor-Critic
Graph annotation generative adversarial networks
Support vector machines with indefinite kernels
Averaged Naive Bayes Trees: A New Extension of AODE
Interval Insensitive Loss for Ordinal Classification
A Model of Text-Enhanced Knowledge Graph Representation Learning with Collaborative Attention
Constructing a Knowledge-Guided Mental Health Chatbot with LLMs
A State Aggregation Approach for Solving Knapsack Problem with Deep Reinforcement Learning
Theory of Mind with Guilt Aversion Facilitates Cooperative Reinforcement Learning
Continuous Target Shift Adaptation in Supervised Learning
Self-Weighted Multi-View Clustering with Deep Matrix Factorization
Dude: Dual Distribution-Aware Context Prompt Learning For Large Vision-Language Model
Bayesian neural network unit priors and generalized Weibull-tail property
BarlowRL: Barlow Twins for Data-Efficient Reinforcement Learning
Understanding More Knowledge Makes the Transformer Perform Better in Document-level Relation Extraction
ColorMamba: Towards High-quality NIR-to-RGB Spectral Translation with Mamba
Cascaded and Dual: Discrimination Oriented Network for Brain Tumor Classification
Improving Statute Prediction via Mining Correlations between Statutes
Learning Algorithms for Domain Adaptation
Sliced Wasserstein variational inference
Nuclei segmentation by using convolutional network with distance map and contour information
Learning to Sample Hard Instances for Graph Algorithms
ST-GAN: Unsupervised Facial Image Semantic Transformation Using Generative Adversarial Networks
Bias-tolerant Fair Classification
An Aligned Subgraph Kernel Based on Discrete-Time Quantum Walk
Attentive Path Combination for Knowledge Graph Completion
Learning with Domain Knowledge to Develop Justifiable Convolutional Networks
Kernelized multi-graph matching
Convolutional Neural Collaborative Filtering with Stacked Embeddings
Skew-symmetrically perturbed gradient flow for convex optimization
Run2Survive: A Decision-theoretic Approach to Algorithm Selection based on Survival Analysis
Linear Approximation to ADMM for MAP inference
Structured Denoising Autoencoder for Fault Detection and Analysis
Augment to Interpret: Unsupervised and Inherently Interpretable Graph Embeddings
SPoD-Net: Fast Recovery of Microscopic Images Using Learned ISTA
Learning to Aggregate: Tackling the Aggregation/Disaggregation Problem for OWA
Structured Gaussian Processes with Twin Multiple Kernel Learning
Learning Code Changes by Exploiting Bidirectional Converting Deviation
Robust Domain Randomised Reinforcement Learning through Peer-to-Peer Distillation
FusionU-Net: U-Net with Enhanced Skip Connection for Pathology Image Segmentation
Semi-supervised Convolutional Neural Networks for Identifying Wi-Fi Interference Sources
Ada 2 NPT: An Adaptive Nearest Proxies Triplet Loss for Attribute-Aware Face Recognition with Adaptively Compacted Feature Learning
A Hierarchical Face Recognition Algorithm
Provably Robust and Plausible Counterfactual Explanations for Neural Networks via Robust Optimisation
Learning to Augment with Feature Side-information
Collaborative Recurrent Neural Networks for Dynamic Recommender Systems
G-UAP: Generic Universal Adversarial Perturbation that Fools RPN-based Detectors
Deep Multi-instance Learning with Dynamic Pooling
Non-asymptotic Analysis of Compressive Fisher Discriminants in terms of the Effective Dimension
Improving Gaussian mixture latent variable model convergence with Optimal Transport
Robust Transfer Learning for Active Level Set Estimation with Locally Adaptive Gaussian Process Prior
DENL: Diverse Ensemble and Noisy Logits for Improved Robustness of Neural Networks
Improving Distributed Word Representation and Topic Model by Word-Topic Mixture Model
LPNER: Label Prompt for Few-shot Nested Named Entity Recognition
Conditional Density Estimation with Class Probability Estimators
Asian Conference on Machine Learning, 5-8 December 2024, Hanoi, Vietnam
Multi-Scale Visual Semantics Aggregation with Self-Attention for End-to-End Image-Text Matching
Faster Target Encirclement with Utilization of Obstacles via Multi-Agent Reinforcement Learning
Robust Multi-Agent Reinforcement Learning for Autonomous Vehicle in Noisy Highway Environments
Adaptive Sampling Scheme for Learning in Severely Imbalanced Large Scale Data
Patch-level Neighborhood Interpolation: A General and Effective Graph-based Regularization Strategy
ContriQ: Ally-Focused Cooperation and Enemy-Concentrated Confrontation in Multi-Agent Reinforcement Learning
Enhancing DETRs for Small Object Detection via Multi-Scale Refinement and Query-Aided Mining
Foolproof Cooperative Learning
Pic@Point: Cross-Modal Learning by Local and Global Point-Picture Correspondence
Asian Conference on Machine Learning, ACML 2022, 12-14 December 2022, Hyderabad, India
Multi-Scale Anomaly Detection for Time Series with Attention-based Recurrent Autoencoders
NENN: Incorporate Node and Edge Features in Graph Neural Networks
Asian Conference on Machine Learning, ACML 2021, 17-19 November 2021, Virtual Event
Fast Collaborative Filtering from Implicit Feedback with Provable Guarantees
Robust Regression for Monocular Depth Estimation
Dynamic Coordination Graph for Cooperative Multi-Agent Reinforcement Learning
DALE: Differential Accumulated Local Effects for efficient and accurate global explanations
Learning Continuous-Time Information Diffusion Model for Social Behavioral Data Analysis
Improve Diverse Commonsense Generation by Enhancing Subgraphs
Learnability of Non-I.I.D
Robust Deep Ordinal Regression under Label Noise
A Scalable Heterogeneous Parallel SOM Based on MPI/CUDA
Proximal Average Approximated Incremental Gradient Method for Composite Penalty Regularized Empirical Risk Minimization
Refining Visual Perception for Decoration Display: A Self-Enhanced Deep Captioning Model
Localized Multiple Kernel Learning - A Convex Approach
Rethinking Literary Plagiarism in LLMs through the Lens of Copyright Laws
A Multi-Surrogate Assisted Salp Swarm Feature Selection Algorithm with Multi-Population Adaptive Generation Strategy for Classification
On PAC Learning Halfspaces in Non-interactive Local Privacy Model with Public Unlabeled Data
DCoT: Dual Chain-of-Thought Prompting for Large Multimodal Models
Ordinal Random Fields for Recommender Systems
InfantCryNet: A Data-driven Framework for Intelligent Analysis of Infant Cries
Multi-Task Network Guided Multimodal Fusion for Fake News Detection
Universal Video Face Restoration Method Based on Vision-Language Model
Unleashing the Power of High-pass Filtering in Continuous Graph Neural Networks
Second Order Online Collaborative Filtering
Learning with Augmented Multi-Instance View
Discriminative Feature Representation for Person Re-identification by Batch-contrastive Loss
Optimal Nonlinearities Improve Generalization Performance of Random Features
Towards Human-Like RL: Taming Non-Naturalistic Behavior in Deep RL via Adaptive Behavioral Costs in 3D Games
Probabilistic Fusion of Neural Networks that Incorporates Global Information
Meta-Model-Based Meta-Policy Optimization
One Class Splitting Criteria for Random Forests
Robust Blind Watermarking Framework for Hybrid Networks Combining CNN and Transformer
Reinforcement learning with value advice
Solving Machine Learning Problems
Q-Match: Self-Supervised Learning by Matching Distributions Induced by a Queue
Scale-Invariant Recognition by Weight-Shared CNNs in Parallel
Ensembling With a Fixed Parameter Budget: When Does It Help and Why?
Clustering Uncertain Graphs with Node Attributes
Trust Region Sequential Variational Inference
Deep Embedded Clustering with Data Augmentation
On multi-class classification through the minimization of the confusion matrix norm
Localizing and Amortizing: Efficient Inference for Gaussian Processes
Ted: Tree delineation with reduced dimensions using entropy and deep learning
Constrained Reinforcement Learning via Policy Splitting
Outlier Robust Adversarial Training
Hybrid Estimation for Open-Ended Questions with Early-Age Students' Block-Based Programming Answers
Construction of Incoherent Dictionaries via Direct Babel Function Minimization
Density Ratio Estimation: A New Versatile Tool for Machine Learning
Degree-based stratification of nodes in Graph Neural Networks
TSMCR: Two-stage Supervised Multi-modality Contrastive Representation for Ultrasound-based Breast Cancer Diagnosis
Fast Dynamic Convolutional Neural Networks for Visual Tracking
A New Look at Nearest Neighbours: Identifying Benign Input Geometries via Random Projections
Recognizing Art Style Automatically in Painting with Deep Learning
Geometry-aware stationary subspace analysis
Hierarchical Probabilistic Matrix Factorization with Network Topology for Multi-relational Social Network
Frequency-dependent Image Reconstruction Error for Micro Defect Detection
Preface / Frontmatter
Regularizing Neural Networks via Stochastic Branch Layers
Mitigating Bias: Enhancing Image Classification by Improving Model Explanations
Modelling Symbolic Music: Beyond the Piano Roll
DPOQ: Dynamic Precision Onion Quantization
BRAC+: Improved Behavior Regularized Actor Critic for Offline Reinforcement Learning
Learning Parts-based Representations with Nonnegative Restricted Boltzmann Machine
NAS-HPO-Bench-II: A Benchmark Dataset on Joint Optimization of Convolutional Neural Network Architecture and Training Hyperparameters
Data-Guided Approach for Learning and Improving User Experience in Computer Networks
AFRNN: Stable RNN with Top Down Feedback and Antisymmetry
Polynomial Runtime Bounds for Fixed-Rank Unsupervised Least-Squares Classification
Zero-Reference Lighting Estimation Diffusion Model for Low-Light Image Enhancement
Computer Assisted Composition with Recurrent Neural Networks
Towards Calibrated Losses for Adversarial Robust Reject Option Classification
Learning from Survey Training Samples: Rate Bounds for Horvitz-Thompson Risk Minimizers
DataFrame QA: A Universal LLM Framework on DataFrame Question Answering Without Data Exposure
Countering Relearning with Perception Revising Unlearning
Slice-sampling based 3D Object Classification
Mining Multi-label Concept-Drifting Data Streams Using Dynamic Classifier Ensemble
A Data Driven Approach to Predicting Rating Scores for New Restaurants
Regularized Policy Gradients: Direct Variance Reduction in Policy Gradient Estimation
Linear Time Model Selection for Mixture of Heterogeneous Components
A Mutual Information Regularization for Adversarial Training
Physics-inspired Learning for Structure-Aware Texture-Sensitive Underwater Image Enhancement
Time-Constrained Multi-Agent Path Finding in Non-Lattice Graphs with Deep Reinforcement Learning
AMG-AVSR: Adaptive Modality Guidance for Audio-Visual Speech Recognition via Progressive Feature Enhancement
Sinusoidal Flow: A Fast Invertible Autoregressive Flow
A Study on Trust Region Update Rules in Newton Methods for Large-scale Linear Classification
Select-and-Evaluate: A Learning Framework for Large-Scale Knowledge Graph Search
An Attentive Memory Network Integrated with Aspect Dependency for Document-Level Multi-Aspect Sentiment Classification
VMLC: Statistical Process Control for Image Classification in Manufacturing
Autonomous Myocardial Infarction Detection from Electrocardiogram with a Multi Label Classification Approach
Bayesian Masking: Sparse Bayesian Estimation with Weaker Shrinkage Bias
Exploration vs Exploitation vs Safety: Risk-Aware Multi-Armed Bandits
Unconfused Ultraconservative Multiclass Algorithms
Streaming Variational Inference for Dirichlet Process Mixtures
Contrastive Inductive Bias Controlling Networks for Reinforcement Learning
Boosting Dynamic Programming with Neural Networks for Solving NP-hard Problems
Attributed Graph Subspace Clustering with Graph-Boosting
Data sparse nonparametric regression with ε-insensitive losses
Learning 2-opt Heuristics for the Traveling Salesman Problem via Deep Reinforcement Learning
On the Flatness of Loss Surface for Two-layered ReLU Networks
A Covariance Matrix Adaptation Evolution Strategy for Direct Policy Search in Reproducing Kernel Hilbert Space
On the expressivity of bi-Lipschitz normalizing flows
EPMC: Every Visit Preference Monte Carlo for Reinforcement Learning
Domain Adaptive YOLO for One-Stage Cross-Domain Detection
FedDGL: Federated Dynamic Graph Learning for Temporal Evolution and Data Heterogeneity
Perturbing Eigenvalues with Residual Learning in Graph Convolutional Neural Networks
Remote Wildfire Detection using Multispectral Satellite Imagery and Vision Transformers
Investigating the effect of novel classes in semi-supervised learning
Nested LSTMs
Diffusion-based Visual Representation Learning for Medical Question Answering
Overcoming catastrophic forgetting with classifier expander
Detecting and Repairing Deviated Outputs of Compressed Models
Prompting vision-language fusion for Zero-Shot Composed Image Retrieval
Meta-forests: Domain generalization on random forests with meta-learning
Probing Traffic Trend Forecasting via Spatial-Temporal Aware Learning-Graph Attention
Clustering Induced Kernel Learning
Learning Interpretable Models using Soft Integrity Constraints
PFedAtt: Attention-based Personalized Federated Learning on Heterogeneous Clients
Self-Paced Multi-Label Learning with Diversity
Unsupervised Heterogeneous Domain Adaptation with Sparse Feature Transformation
Towards Maximum Likelihood: Learning Undirected Graphical Models using Persistent Sequential Monte Carlo
Pyramid Correlation based Deep Hough Voting for Visual Object Tracking
Value Function Approximations via Kernel Embeddings for No-Regret Reinforcement Learning
Asian Conference on Machine Learning, ACML 2013, Canberra, ACT, Australia, November 13-15, 2013
Towards Data-Free Domain Generalization
CTAB-GAN: Effective Table Data Synthesizing
QActor: Active Learning on Noisy Labels
SDC-causing Error Detection Based on Lightweight Vulnerability Prediction
Prediction of Crowd Flow in City Complex with Missing Data
Online matrix prediction for sparse loss matrices
Joint Patch-Group Based Sparse Representation for Image Inpainting
Transfer Learning with Adaptive Online TrAdaBoost for Data Streams
Functional Isolation Forest
Fast Stealthily Biased Sampling Using Sliced Wasserstein Distance
Probabilistic Adaptive Spatial-Temporal Regularized Correlation Filters for UAV Tracking
ProtoDiffusion: Classifier-Free Diffusion Guidance with Prototype Learning
Efficient Coreset Constructions via Sensitivity Sampling
Reinforcement Learning for Solving Stochastic Vehicle Routing Problem
Whitening-Free Least-Squares Non-Gaussian Component Analysis
Sparsity on Statistical Simplexes and Diversity in Social Ranking
Cross-Domain Relation Adaptation
Class-prior Estimation for Learning from Positive and Unlabeled Data
GWQ: Group-Wise Quantization Framework for Neural Networks
Distributionally Robust Groupwise Regularization Estimator
Position-dependent partial convolutions for supervised spatial interpolation
SecureNets: Secure Inference of Deep Neural Networks on an Untrusted Cloud
A Quantum-Inspired Ensemble Method and Quantum-Inspired Forest Regressors
A New Perspective On the Expressive Equivalence Between Graph Convolution and Attention Models
Maximization of Monotone k-Submodular Functions with Bounded Curvature and Non-k-Submodular Functions
Probability Calibration Trees
Improving Sybil Detection via Graph Pruning and Regularization Techniques
A Corrected Expected Improvement Acquisition Function Under Noisy Observations
Pseudo-reward Algorithms for Contextual Bandits with Linear Payoff Functions
Vector Transport Free Riemannian LBFGS for Optimization on Symmetric Positive Definite Matrix Manifolds
Forward-Backward Generative Adversarial Networks for Anomaly Detection
A Novel Graph Aggregation Method Based on Feature Distribution Around Each Ego-node for Heterophily
An online semi-definite programming with a generalised log-determinant regularizer and its applications
Learning to Switch Optimizers for Quadratic Programming
Evolutionary Neural Architecture Search for Multivariate Time Series Forecasting
Magnitude-Preserving Ranking for Structured Outputs
Theoretical Analyses on Ensemble and Multiple Kernel Regressors
Learning Predictive Leading Indicators for Forecasting Time Series Systems with Unknown Clusters of Forecast Tasks
Latent Multi-view Semi-Supervised Classification
Multiple Imputation with Neural Network Gaussian Process for High-dimensional Incomplete Data
A Partial Label Metric Learning Algorithm for Class Imbalanced Data
Feature Selection via Maximizing Neighborhood Soft Margin
Pyramid Person Matching Network for Person Re-identification
A UCB-Like Strategy of Collaborative Filtering
Distinguishing Question Subjectivity from Difficulty for Improved Crowdsourcing
Building Decision Tree for Imbalanced Classification via Deep Reinforcement Learning
Augmenting Imbalanced Time-series Data via Adversarial Perturbation in Latent Space
Multiple Kernel Learning with Data Augmentation
KURL: A Knowledge-Guided Reinforcement Learning Model for Active Object Tracking
How Classification Baseline Works for Deep Metric Learning: A Perspective of Metric Space
Knowledge Guided Multi-instance Multi-label Learning via Neural Networks in Medicines Prediction
Using Deep Neural Networks to Automate Large Scale Statistical Analysis for Big Data Applications
PSForest: Improving Deep Forest via Feature Pooling and Error Screening
Learning with Interactive Models over Decision-Dependent Distributions
Learning Dynamic Context Graph Embedding
Aggregating Predictions via Sequential Mini-Trading
Graph Neural Networks (with Proper Weights) Can Escape Oversmoothing
Forward and Backward Knowledge Transfer for Sentiment Classification
An Enhanced Human Activity Recognition Algorithm with Positional Attention
Asian Conference on Machine Learning, ACML 2023, 11-14 November 2023, Istanbul, Turkey
Better Loss Landscape Visualization for Deep Neural Networks with Trajectory Information
Pedestrian Wind Factor Estimation in Complex Urban Environments
Building a Decision Cluster Forest Model to Classify High Dimensional Data with Multi-classes
Deep Representation Learning for Prediction of Temporal Event Sets in the Continuous Time Domain
Differentially Private Deep Learning with Importance-based Adaptive Gradient Processing
How GAN Generators can Invert Networks in Real-Time
A Two-Stage Training Framework with Feature-Label Matching Mechanism for Learning from Label Proportions
Accelerated Coordinate Descent with Adaptive Coordinate Frequencies
Cost-Sensitive Boosting: Fitting an Additive Asymmetric Logistic Regression Model
Focused Anchors Loss: cost-sensitive learning of discriminative features for imbalanced classification
Towards Better Explanations for Object Detection
CVaR-Regret Bounds for Multi-armed Bandits
RedditEM: Unveiling Diachronic Semantic Shifts in Social Network Discourse
Fast Randomized PCA for Sparse Data
Real-time tree search with pessimistic scenarios: Winning the NeurIPS 2018 Pommerman Competition
Max-Utility Based Arm Selection Strategy For Sequential Query Recommendations
Sample Distillation for Object Detection and Image Classification
A Fast Hierarchical Alternating Least Squares Algorithm for Orthogonal Nonnegative Matrix Factorization
calibrated adversarial training
Variance Reduced Online Gradient Descent for Kernelized Pairwise Learning with Limited Memory
On the sample complexity of privately learning half-spaces
A One-step Approach to Covariate Shift Adaptation
Fusing Recalibrated Features and Depthwise Separable Convolution for the Mangrove Bird Sound Classification
A Reformulation of Support Vector Machines for General Confidence Functions
Active Change-Point Detection
Long-Range Graph U-Nets: Node and Edge Clustering Pooling Model For Stroke Classification in Online Handwritten Documents
Deep Learning with a Rethinking Structure for Multi-label Classification
Diffusion Model Based Posterior Sampling for Noisy Linear Inverse Problems
Autoencoder Trees
Robust Document Distance with Wasserstein-Fisher-Rao metric
Auto-Physics-Encoder: Using Physics-Informed Latent Layer Two-Way Physics Flow for Monitoring Systems with Unobservability
Learning a Metric Space for Neighbourhood Topology Estimation: Application to Manifold Learning
Multi-view Clustering with Adaptively Learned Graph
Deep Reinforcement Learning for High-Frequency Market Making
Proper Inner Product with Mean Displacement for Gaussian Noise Invariant ICA
LADet: A Light-weight and Adaptive Network for Multi-scale Object Detection
Network Representation Learning Algorithm Based on Neighborhood Influence Sequence
Geometry-Aware Principal Component Analysis for Symmetric Positive Definite Matrices
Edit-A-Video: Single Video Editing with Object-Aware Consistency
A Self-improving Skin Lesions Diagnosis Framework Via Pseudo-labeling and Self-distillation
Dual online inference for latent Dirichlet allocation
Enhancing Cross-Category Learning in Recommendation Systems with Multi-Layer Embedding Training
Multi-stream based marked point process
Online Passive Aggressive Active Learning and Its Applications
Constrained Density Matching and Modeling for Cross-lingual Alignment of Contextualized Representations
Distilling Influences to Mitigate Prediction Churn in Graph Neural Networks
Stochastic Gradient Trees
Bridging Ordinary-Label Learning and Complementary-Label Learning
EENAS: An Efficient Evolutionary Algorithm for Neural Architecture Search
Bayesian Latent Factor Model for Higher-order Data
Knowledge Graph Large Language Model (KG-LLM) for Link Prediction
Multi-objective Adaptive Dynamics Attention Model to Solve Multi-objective Vehicle Routing Problem
CHS-NET: A Cascaded Neural Network with Semi-Focal Loss for Mitosis Detection
Beyond L p Clipping: Equalization based Psychoacoustic Attacks against ASRs
Novel Boosting Frameworks to Improve the Performance of Collaborative Filtering
On the Interpretability of Attention Networks
Estimation of Counterfactual Interventions under Uncertainties
Software Component Prediction for Bug Reports
Bank of Weight Filters for Deep CNNs
Consistency of structured output learning with missing labels
PISDR: Page and Item Sequential Decision for Re-ranking Based on Offline Reinforcement Learning
Generating Deep Networks Explanations with Robust Attribution Alignment
An Efficient Approach for Multi-Sentence Compression
Robust computation of optimal transport by β-potential regularization
Underwater Image Restoration Based on Convolutional Neural Network
Long Short-term Memory Network over Rhetorical Structure Theory for Sentence-level Sentiment Analysis
Deep Correlation Structure Preserved Label Space Embedding for Multi-label Classification
Context-Aware Online Commercial Intention Detection
Surface Reconstruction based on Self-Merging Octree with Deep Learning
Bidirectional Dependency-Guided Attention for Relation Extraction
Injecting Structured Data to Generative Topic Model in Enterprise Settings
Learning Convolutional Neural Networks using Hybrid Orthogonal Projection and Estimation
Partially Observable Markov Decision Process Modelling for Assessing Hierarchies
LabelPrompt: Effective prompt-based learning for relation classification
End-to-End Time Series Imputation via Residual Short Paths
A Novel Differentiable Mixed-Precision Quantization Search Framework for Alleviating the Matthew Effect and Improving Robustness
AIIR-MIX: Multi-Agent Reinforcement Learning Meets Attention Individual Intrinsic Reward Mixing Network
Nighttime Semantic Segmentation with Unsupervised Learning and Cross Attention
Exemplar Based Mixture Models with Censored Data
Enhancing Aspect Sentiment Quad Prediction through Dual-Sequence Data Augmentation and Contrastive Learning
Profitable Bandits
Extracting Invariant Features From Images Using An Equivariant Autoencoder
Effective Sentence Scoring Method Using BERT for Speech Recognition
Feature-correlation-aware Gaussian Process Latent Variable Model
Random Projection in Neural Episodic Control
Self-Supervised Deep Multi-View Subspace Clustering
Learning Maximum Margin Markov Networks from examples with missing labels