yusuke1997/dblp-id-title huggingface dataset:
AutoBSS: An Efficient Algorithm for Block Stacking Style Search
Exploiting easy data in online optimization
Unsupervised Keypoint Learning for Guiding Class-Conditional Video Prediction
SymILO: A Symmetry-Aware Learning Framework for Integer Linear Optimization
Integer Discrete Flows and Lossless Compression
Probabilistic n-Choose-k Models for Classification and Ranking
Towards a Unified Framework of Contrastive Learning for Disentangled Representations
Precise Learning Curves and Higher-Order Scalings for Dot-product Kernel Regression
Bridge the Points: Graph-based Few-shot Segment Anything Semantically
Robust Spatial Filtering with Beta Divergence
Functional Regularization for Representation Learning: A Unified Theoretical Perspective
Analysis of Drifting Dynamics with Neural Network Hidden Markov Models
Pseudo-Extended Markov chain Monte Carlo
Self-supervised Auxiliary Learning with Meta-paths for Heterogeneous Graphs
Reverse KL-Divergence Training of Prior Networks: Improved Uncertainty and Adversarial Robustness
Hierarchical Patch VAE-GAN: Generating Diverse Videos from a Single Sample
Differentially Private Learning with Adaptive Clipping
A Probabilistic Approach to Language Change
Co-regularized Multi-view Spectral Clustering
Continuous-time Value Function Approximation in Reproducing Kernel Hilbert Spaces
Improved Techniques for Training Score-Based Generative Models
Large scale networks fingerprinting and visualization using the k-core decomposition
Hierarchical Clustering Beyond the Worst-Case
A Transformer-Based Object Detector with Coarse-Fine Crossing Representations
Phonetic Classification and Recognition Using the Multi-Layer Perceptron
Sequence-Augmented SE(3)-Flow Matching For Conditional Protein Generation
Efficient and Modular Implicit Differentiation
Security Analysis of Safe and Seldonian Reinforcement Learning Algorithms
An Improved Analysis and Rates for Variance Reduction under Without-replacement Sampling Orders
Unification of Information Maximization and Minimization
Dual Adversarial Semantics-Consistent Network for Generalized Zero-Shot Learning
MetaLA: Unified Optimal Linear Approximation to Softmax Attention Map
First-Order Adaptive Sample Size Methods to Reduce Complexity of Empirical Risk Minimization
On Privacy and Personalization in Cross-Silo Federated Learning
ETO: Efficient Transformer-based Local Feature Matching by Organizing Multiple Homography Hypotheses
SuperLoss: A Generic Loss for Robust Curriculum Learning
Particle-based Variational Inference with Generalized Wasserstein Gradient Flow
Towards Deeper Graph Neural Networks with Differentiable Group Normalization
Confidence sequences for sampling without replacement
Statistical Regeneration Guarantees of the Wasserstein Autoencoder with Latent Space Consistency
Diffusion Probabilistic Models for Structured Node Classification
Learning Sparse Image Codes using a Wavelet Pyramid Architecture
Stochastic Online Greedy Learning with Semi-bandit Feedbacks
Generative Neural Machine Translation
A Precise Characterization of the Class of Languages Recognized by Neural Nets under Gaussian and Other Common Noise Distributions
Stochastic Online AUC Maximization
Algorithms for Interdependent Security Games
Video Prediction Models as Rewards for Reinforcement Learning
Locally Private and Robust Multi-Armed Bandits
SceneDiffuser: Efficient and Controllable Driving Simulation Initialization and Rollout
Offline Reinforcement Learning with OOD State Correction and OOD Action Suppression
Human Parsing Based Texture Transfer from Single Image to 3D Human via Cross-View Consistency
Nearest-Neighbor-Based Active Learning for Rare Category Detection
Analog Implementation of Shunting Neural Networks
Beyond Redundancy: Information-aware Unsupervised Multiplex Graph Structure Learning
Support Vector Classification with Input Data Uncertainty
Memory Replay GANs: Learning to Generate New Categories without Forgetting
Slow Learners are Fast
Universal Sample Coding
Towards Effective Multi-Modal Interchanges in Zero-Resource Sounding Object Localization
Dropping Symmetry for Fast Symmetric Nonnegative Matrix Factorization
Superposition of many models into one
Analysis and Comparison of Different Learning Algorithms for Pattern Association Problems
SEAL: Self-supervised Embodied Active Learning using Exploration and 3D Consistency
Characterizing the risk of fairwashing
Knowledge Transfer in Multi-Task Deep Reinforcement Learning for Continuous Control
Continual Unsupervised Representation Learning
Minimax Estimation of Maximum Mean Discrepancy with Radial Kernels
Unelicitable Backdoors via Cryptographic Transformer Circuits
Online Neural Connectivity Estimation with Noisy Group Testing
A New Approach to Hybrid HMM/ANN Speech Recognition using Mutual Information Neural Networks
Data Attribution for Text-to-Image Models by Unlearning Synthesized Images
VLMbench: A Compositional Benchmark for Vision-and-Language Manipulation
Data Skeletonization via Reeb Graphs
Consistent Estimation for PCA and Sparse Regression with Oblivious Outliers
Interactive Label Cleaning with Example-based Explanations
Cloud Object Detector Adaptation by Integrating Different Source Knowledge
A central limit theorem with application to inference in \(\alpha\)-stable regression models
Near-optimal sample compression for nearest neighbors
On the Correctness and Sample Complexity of Inverse Reinforcement Learning
Tighter Convergence Bounds for Shuffled SGD via Primal-Dual Perspective
Encoding Geometric Invariances in Higher-Order Neural Networks
Universal Prompt Tuning for Graph Neural Networks
Semi-Supervised Domain Adaptation with Non-Parametric Copulas
Space-Variant Single-Image Blind Deconvolution for Removing Camera Shake
Kernels on Structured Objects Through Nested Histograms
Uncertainty-Aware Reinforcement Learning for Risk-Sensitive Player Evaluation in Sports Game
Worst-Case Linear Discriminant Analysis
Fast samplers for Inverse Problems in Iterative Refinement models
Implicit Regularization in Deep Learning May Not Be Explainable by Norms
Augur: Data-Parallel Probabilistic Modeling
VISA: Variational Inference with Sequential Sample-Average Approximations
Online Sinkhorn: Optimal Transport distances from sample streams
Semi-Supervised Learning with Trees
Efficient RL with Impaired Observability: Learning to Act with Delayed and Missing State Observations
Ex Uno Pluria: Insights on Ensembling in Low Precision Number Systems
Simulations Suggest Information Processing Roles for the Diverse Currents in Hippocampal Neurons
Neural Auto-Curricula in Two-Player Zero-Sum Games
Kernels on Attributed Pointsets with Applications
Discriminant Saliency for Visual Recognition from Cluttered Scenes
The Statistical Mechanics of k-Satisfaction
Parallel Optimization of Motion Controllers via Policy Iteration
Mutual information for symmetric rank-one matrix estimation: A proof of the replica formula
Ecosystem-level Analysis of Deployed Machine Learning Reveals Homogeneous Outcomes
ShapeCrafter: A Recursive Text-Conditioned 3D Shape Generation Model
Joint Active Feature Acquisition and Classification with Variable-Size Set Encoding
Bayesian Distributed Stochastic Gradient Descent
Exposing and Exploiting Fine-Grained Block Structures for Fast and Accurate Sparse Training
Parallelizing Model-based Reinforcement Learning Over the Sequence Length
Beyond Prompts: Dynamic Conversational Benchmarking of Large Language Models
When Do Graph Neural Networks Help with Node Classification? Investigating the Homophily Principle on Node Distinguishability
Hyperparameter Learning via Distributional Transfer
GStarX: Explaining Graph Neural Networks with Structure-Aware Cooperative Games
MixFormerV2: Efficient Fully Transformer Tracking
A survey and benchmark of high-dimensional Bayesian optimization of discrete sequences
Revisiting Scalarization in Multi-Task Learning: A Theoretical Perspective
Audio-Visual Sound Separation Via Hidden Markov Models
Real World Games Look Like Spinning Tops
A Game-Theoretic Analysis of the Empirical Revenue Maximization Algorithm with Endogenous Sampling
Estimating Mutual Information for Discrete-Continuous Mixtures
When and How to Lift the Lockdown? Global COVID-19 Scenario Analysis and Policy Assessment using Compartmental Gaussian Processes
Low-Rank Time-Frequency Synthesis
Exploring Cross-Video and Cross-Modality Signals for Weakly-Supervised Audio-Visual Video Parsing
ClevrTex: A Texture-Rich Benchmark for Unsupervised Multi-Object Segmentation
Second Order Approximations for Probability Models
AUC optimization and the two-sample problem
Neural Networks for Efficient Bayesian Decoding of Natural Images from Retinal Neurons
KSD Aggregated Goodness-of-fit Test
Better Mini-Batch Algorithms via Accelerated Gradient Methods
UKnow: A Unified Knowledge Protocol with Multimodal Knowledge Graph Datasets for Reasoning and Vision-Language Pre-Training
Variational Bayesian Decision-making for Continuous Utilities
On the Trade-off of Intra-/Inter-class Diversity for Supervised Pre-training
Spectral Norm Regularization of Orthonormal Representations for Graph Transduction
SaVeNet: A Scalable Vector Network for Enhanced Molecular Representation Learning
Feature Selection and Classification on Matrix Data: From Large Margins to Small Covering Numbers
A configurable analog VLSI neural network with spiking neurons and self-regulating plastic synapses
EMPATH: Face, Emotion, and Gender Recognition Using Holons
An Extensible Benchmark Suite for Learning to Simulate Physical Systems
Finding Counterfactually Optimal Action Sequences in Continuous State Spaces
Meta-Surrogate Benchmarking for Hyperparameter Optimization
Targeted Adversarial Perturbations for Monocular Depth Prediction
Recognizing Overlapping Hand-Printed Characters by Centered-Object Integrated Segmentation and Recognition
ReactZyme: A Benchmark for Enzyme-Reaction Prediction
Independence Testing-Based Approach to Causal Discovery under Measurement Error and Linear Non-Gaussian Models
A Model for Learning the Semantics of Pictures
Meta-Adapter: An Online Few-shot Learner for Vision-Language Model
PolarStream: Streaming Object Detection and Segmentation with Polar Pillars
Decrypting Cryptic Crosswords: Semantically Complex Wordplay Puzzles as a Target for NLP
Semantic Feature Learning for Universal Unsupervised Cross-Domain Retrieval
Model Based Image Compression and Adaptive Data Representaion by Interacting Filter Banks
Active Gesture Recognition using Learned Visual Attention
Capturing Graphs with Hypo-Elliptic Diffusions
Distributional Reward Decomposition for Reinforcement Learning
Nearly Tight Bounds for the Continuum-Armed Bandit Problem
Causal Discovery from Soft Interventions with Unknown Targets: Characterization and Learning
Bayesian Dyadic Trees and Histograms for Regression
Graded Grammaticality in Prediction Fractal Machines
Rates of Convergence of Performance Gradient Estimates Using Function Approximation and Bias in Reinforcement Learning
Identify Then Recommend: Towards Unsupervised Group Recommendation
A Primal-Dual link between GANs and Autoencoders
Goal Driven Discovery of Distributional Differences via Language Descriptions
Per-Pixel Classification is Not All You Need for Semantic Segmentation
CoBo: Collaborative Learning via Bilevel Optimization
Divide and Couple: Using Monte Carlo Variational Objectives for Posterior Approximation
LAMP: Extracting Text from Gradients with Language Model Priors
Boosting Learning for LDPC Codes to Improve the Error-Floor Performance
Combinatorial Bandits with Relative Feedback
Robust Neural Posterior Estimation and Statistical Model Criticism
Signal Estimation Under Random Time-Warpings and Nonlinear Signal Alignment
Vista: A Generalizable Driving World Model with High Fidelity and Versatile Controllability
Monte Carlo Tree Search based Space Transfer for Black Box Optimization
Correlated Bigram LSA for Unsupervised Language Model Adaptation
Modelling Seasonality and Trends in Daily Rainfall Data
Neural Control for Nonlinear Dynamic Systems
Double and Single Descent in Causal Inference with an Application to High-Dimensional Synthetic Control
Achievable Fairness on Your Data With Utility Guarantees
Statistical Efficiency of Thompson Sampling for Combinatorial Semi-Bandits
Convex Relaxations for Permutation Problems
Non-iterative Estimation with Perturbed Gaussian Markov Processes
Convex-Concave Min-Max Stackelberg Games
Sampling from Structured Log-Concave Distributions via a Soft-Threshold Dikin Walk
D2R2: Diffusion-based Representation with Random Distance Matching for Tabular Few-shot Learning
Hierarchical Semi-Implicit Variational Inference with Application to Diffusion Model Acceleration
Multiple-Step Greedy Policies in Approximate and Online Reinforcement Learning
A Generalized Natural Actor-Critic Algorithm
Matrix Completion From any Given Set of Observations
Reducing Adversarially Robust Learning to Non-Robust PAC Learning
Coordinates Are NOT Lonely - Codebook Prior Helps Implicit Neural 3D representations
Self-Paced Contrastive Learning for Semi-supervised Medical Image Segmentation with Meta-labels
Statistical Mechanics of Temporal Association in Neural Networks
State Abstraction in MAXQ Hierarchical Reinforcement Learning
Congruence between model and human attention reveals unique signatures of critical visual events
Neural Network Model of Semantic Processing in the Remote Associates Test
Harmonizing Stochasticity and Determinism: Scene-responsive Diverse Human Motion Prediction
A Comparison of Discrete-Time Operator Models and for Nonlinear System Identification
Generative Modeling through the Semi-dual Formulation of Unbalanced Optimal Transport
Mistake Bounds for Binary Matrix Completion
MambaLRP: Explaining Selective State Space Sequence Models
Efficient Optimization for Average Precision SVM
3D Pose Transfer with Correspondence Learning and Mesh Refinement
The Randomized Midpoint Method for Log-Concave Sampling
Switching Temporary Teachers for Semi-Supervised Semantic Segmentation
PhysGNN: A Physics-Driven Graph Neural Network Based Model for Predicting Soft Tissue Deformation in Image-Guided Neurosurgery
DABS: a Domain-Agnostic Benchmark for Self-Supervised Learning
Bayesian Video Shot Segmentation
Aligning individual brains with fused unbalanced Gromov Wasserstein
SGD vs GD: Rank Deficiency in Linear Networks
Warm-up Free Policy Optimization: Improved Regret in Linear Markov Decision Processes
Sample based Explanations via Generalized Representers
Statistical Optimal Transport posed as Learning Kernel Embedding
Clifford Group Equivariant Neural Networks
DisenGCD: A Meta Multigraph-assisted Disentangled Graph Learning Framework for Cognitive Diagnosis
SearchLVLMs: A Plug-and-Play Framework for Augmenting Large Vision-Language Models by Searching Up-to-Date Internet Knowledge
HMM Speech Recognition with Neural Net Discrimination
Temporally Asymmetric Hebbian Learning, Spike liming and Neural Response Variability
Occlusive Components Analysis
Learning Transformational Invariants from Natural Movies
Aggregating Quantitative Relative Judgments: From Social Choice to Ranking Prediction
A Unified Framework for Deep Symbolic Regression
Bridging the Gap from Asymmetry Tricks to Decorrelation Principles in Non-contrastive Self-supervised Learning
Selective compression learning of latent representations for variable-rate image compression
On Tractable Computation of Expected Predictions
ToAlign: Task-Oriented Alignment for Unsupervised Domain Adaptation
DACO: Towards Application-Driven and Comprehensive Data Analysis via Code Generation
Beta Embeddings for Multi-Hop Logical Reasoning in Knowledge Graphs
An Empirical Study Towards Prompt-Tuning for Graph Contrastive Pre-Training in Recommendations
Binarized Neural Networks
Bayesian filtering unifies adaptive and non-adaptive neural network optimization methods
Video-to-Video Synthesis
Neural Taskonomy: Inferring the Similarity of Task-Derived Representations from Brain Activity
ViTAE: Vision Transformer Advanced by Exploring Intrinsic Inductive Bias
HydraViT: Stacking Heads for a Scalable ViT
Neural Ensemble Search for Uncertainty Estimation and Dataset Shift
Dynamic Non-monotone Submodular Maximization
Equivariant flow matching
Learning Riemannian metric for disease progression modeling
Sharp Impossibility Results for Hyper-graph Testing
The Flajolet-Martin Sketch Itself Preserves Differential Privacy: Private Counting with Minimal Space
Iterative Reachability Estimation for Safe Reinforcement Learning
Effiicient BackProp
General Low-rank Matrix Optimization: Geometric Analysis and Sharper Bounds
Multi-Head Mixture-of-Experts
Memory-Constrained Algorithms for Convex Optimization
Don't blame Dataset Shift! Shortcut Learning due to Gradients and Cross Entropy
Emergence of Movement Sensitive Neurons' Properties by Learning a Sparse Code for Natural Moving Images
Benchmarking Encoder-Decoder Architectures for Biplanar X-ray to 3D Bone Shape Reconstruction
Structural Analysis of Branch-and-Cut and the Learnability of Gomory Mixed Integer Cuts
An Optimization Method of Layered Neural Networks based on the Modified Information Criterion
Learning Positive Functions with Pseudo Mirror Descent
ICE-BeeM: Identifiable Conditional Energy-Based Deep Models Based on Nonlinear ICA
Guaranteed Conservation of Momentum for Learning Particle-based Fluid Dynamics
SLED: Self Logits Evolution Decoding for Improving Factuality in Large Language Models
A Simple Approach to Automated Spectral Clustering
GLIME: General, Stable and Local LIME Explanation
Hash Embeddings for Efficient Word Representations
Representation Costs of Linear Neural Networks: Analysis and Design
Adaptable Agent Populations via a Generative Model of Policies
FleXOR: Trainable Fractional Quantization
ActSort: An active-learning accelerated cell sorting algorithm for large-scale calcium imaging datasets
Great Minds Think Alike: The Universal Convergence Trend of Input Salience
Computing with Infinite Networks
Can Models Learn Skill Composition from Examples?
Regularizing Trajectory Optimization with Denoising Autoencoders
A Matrix Chernoff Bound for Markov Chains and Its Application to Co-occurrence Matrices
Bayesian Bias Mitigation for Crowdsourcing
Efficient and Robust Spiking Neural Circuit for Navigation Inspired by Echolocating Bats
On Computing Pairwise Statistics with Local Differential Privacy
Learning to Cooperate with Humans using Generative Agents
Risk-Averse Fine-tuning of Large Language Models
Non-asymptotic convergence bounds for Wasserstein approximation using point clouds
From Chaos to Clarity: 3DGS in the Dark
Decompose, Analyze and Rethink: Solving Intricate Problems with Human-like Reasoning Cycle
Understanding Diffusion Objectives as the ELBO with Simple Data Augmentation
Hyper-SD: Trajectory Segmented Consistency Model for Efficient Image Synthesis
Clustering with Noisy Queries
Evaluating and Rewarding Teamwork Using Cooperative Game Abstractions
ALMA: Hierarchical Learning for Composite Multi-Agent Tasks
Shape-Based Object Localization for Descriptive Classification
Variational Bayesian Monte Carlo with Noisy Likelihoods
A robust inlier identification algorithm for point cloud registration via 𝓁 0 -minimization
Approximation Ratios of Graph Neural Networks for Combinatorial Problems
Slice sampling normalized kernel-weighted completely random measure mixture models
Bayes Consistency vs. H-Consistency: The Interplay between Surrogate Loss Functions and the Scoring Function Class
Fine-Grained Human Feedback Gives Better Rewards for Language Model Training
Power analysis of knockoff filters for correlated designs
Physics-Regularized Multi-Modal Image Assimilation for Brain Tumor Localization
Beyond Confidence Regions: Tight Bayesian Ambiguity Sets for Robust MDPs
Product Analysis: Learning to Model Observations as Products of Hidden Variables
Precise asymptotics of reweighted least-squares algorithms for linear diagonal networks
Content-based recommendations with Poisson factorization
NeuralSolver: Learning Algorithms For Consistent and Efficient Extrapolation Across General Tasks
Constrained Generation of Semantically Valid Graphs via Regularizing Variational Autoencoders
Multi-language Diversity Benefits Autoformalization
Simple MAP Inference via Low-Rank Relaxations
Multimodal Few-Shot Learning with Frozen Language Models
Intervention Generalization: A View from Factor Graph Models
Training Stronger Baselines for Learning to Optimize
Fantastic Robustness Measures: The Secrets of Robust Generalization
The Surprising Effectiveness of SP Voting with Partial Preferences
Three-dimensional spike localization and improved motion correction for Neuropixels recordings
Robust Bloom Filters for Large MultiLabel Classification Tasks
Can semi-supervised learning use all the data effectively? A lower bound perspective
The Generalization-Stability Tradeoff In Neural Network Pruning
On the Accuracy of Bounded Rationality: How Far from Optimal Is Fast and Frugal?
Position Coupling: Improving Length Generalization of Arithmetic Transformers Using Task Structure
Controlling privacy in recommender systems
Achieving Equalized Odds by Resampling Sensitive Attributes
Pain Evaluation in Video using Extended Multitask Learning from Multidimensional Measurements
Navigating Through Temporal Difference
Causes and Effects of Unanticipated Numerical Deviations in Neural Network Inference Frameworks
FedRolex: Model-Heterogeneous Federated Learning with Rolling Sub-Model Extraction
Neural Networks with Cheap Differential Operators
Revisiting the Integration of Convolution and Attention for Vision Backbone
Recursive Context Propagation Network for Semantic Scene Labeling
Computational Elements of the Adaptive Controller of the Human Arm
Confident Anchor-Induced Multi-Source Free Domain Adaptation
Lifted Inference Seen from the Other Side : The Tractable Features
GSLB: The Graph Structure Learning Benchmark
Extended Bayesian Information Criteria for Gaussian Graphical Models
Scaling Sign Language Translation
Non-convex Finite-Sum Optimization Via SCSG Methods
On Relating Explanations and Adversarial Examples
Mutli-Armed Bandits with Network Interference
CLIP4HOI: Towards Adapting CLIP for Practical Zero-Shot HOI Detection
A Geometric Perspective towards Neural Calibration via Sensitivity Decomposition
Attribute Prototype Network for Zero-Shot Learning
Independent Prototype Propagation for Zero-Shot Compositionality
Fast ε-free Inference of Simulation Models with Bayesian Conditional Density Estimation
Feature-aware Label Space Dimension Reduction for Multi-label Classification
Adaptive Interest for Emphatic Reinforcement Learning
Teaching a GAN What Not to Learn
Learning to Constrain Policy Optimization with Virtual Trust Region
Deep Supervised Discrete Hashing
Weston-Watkins Hinge Loss and Ordered Partitions
Nonparanormal Belief Propagation (NPNBP)
A Continuous Mapping For Augmentation Design
Ease-of-Teaching and Language Structure from Emergent Communication
Inverse Reward Design
Searching for Optimal Per-Coordinate Step-sizes with Multidimensional Backtracking
What is the Inductive Bias of Flatness Regularization? A Study of Deep Matrix Factorization Models
Construction of Hierarchical Neural Architecture Search Spaces based on Context-free Grammars
Revisiting Differentially Private ReLU Regression
On Infinite-Width Hypernetworks
Extending Stein's unbiased risk estimator to train deep denoisers with correlated pairs of noisy images
Fast global convergence rates of gradient methods for high-dimensional statistical recovery
Neurosymbolic Reinforcement Learning with Formally Verified Exploration
Interpolated Policy Gradient: Merging On-Policy and Off-Policy Gradient Estimation for Deep Reinforcement Learning
A MCMC Approach to Hierarchical Mixture Modelling
Resonance in a Stochastic Neuron Model with Delayed Interaction
Contrastive Laplacian Eigenmaps
All Word Embeddings from One Embedding
Counting the Optimal Solutions in Graphical Models
Bilinear classifiers for visual recognition
Optimal Regularized Dual Averaging Methods for Stochastic Optimization
PureGen: Universal Data Purification for Train-Time Poison Defense via Generative Model Dynamics
Non-separable Spatiotemporal Brain Hemodynamics Contain Neural Information