yusuke1997/dblp-id-title huggingface dataset:
Generalization Bounds for Stochastic Gradient Descent via Localized $\varepsilon$-Covers
Fisher Flow Matching for Generative Modeling over Discrete Data
Bayesian Model of Surface Perception
Sample Efficient Stochastic Gradient Iterative Hard Thresholding Method for Stochastic Sparse Linear Regression with Limited Attribute Observation
Training Neural Networks Using Features Replay
High-Dimensional Bayesian Optimization via Nested Riemannian Manifolds
Hollowed Net for On-Device Personalization of Text-to-Image Diffusion Models
Predictive Approximate Bayesian Computation via Saddle Points
A Dataset for Answering Time-Sensitive Questions
Semi-supervised Learning with Weakly-Related Unlabeled Data: Towards Better Text Categorization
Primal-Attention: Self-attention through Asymmetric Kernel SVD in Primal Representation
Spectral Methods for Indian Buffet Process Inference
Synergies in learning words and their referents
Expansion and Shrinkage of Localization for Weakly-Supervised Semantic Segmentation
SpeechForensics: Audio-Visual Speech Representation Learning for Face Forgery Detection
Neural Adaptive Sequential Monte Carlo
Collaborative Score Distillation for Consistent Visual Editing
A Primal-Dual Algorithm for Group Sparse Regularization with Overlapping Groups
Optimal deep learning of holomorphic operators between Banach spaces
Demixed shared component analysis of neural population data from multiple brain areas
Features as Sufficient Statistics
Quasi-Newton Methods for Markov Chain Monte Carlo
Dynamic Ensemble Modeling Approach to Nonstationary Neural Decoding in Brain-Computer Interfaces
SeeA*: Efficient Exploration-Enhanced A* Search by Selective Sampling
The Limits of Learning with Missing Data
Richelieu: Self-Evolving LLM-Based Agents for AI Diplomacy
Uncertainty-based Offline Variational Bayesian Reinforcement Learning for Robustness under Diverse Data Corruptions
Memory Efficient Meta-Learning with Large Images
Reliable Off-Policy Learning for Dosage Combinations
Blind Source Separation via Multinode Sparse Representation
Convolutional Tensor-Train LSTM for Spatio-Temporal Learning
Learning with Algorithmic Supervision via Continuous Relaxations
Blind source separation for over-determined delayed mixtures
Polynomial Codes: an Optimal Design for High-Dimensional Coded Matrix Multiplication
Signal Processing by Multiplexing and Demultiplexing in Neurons
Compact Representation of Uncertainty in Clustering
Laplace Propagation
Identification of Nonlinear Latent Hierarchical Models
Supervising Unsupervised Learning
On the Design of Loss Functions for Classification: theory, robustness to outliers, and SavageBoost
Practical Differentially Private Top-k Selection with Pay-what-you-get Composition
Supervised Clustering
Generalised f-Mean Aggregation for Graph Neural Networks
Structural Inference of Dynamical Systems with Conjoined State Space Models
On Divergence Measures for Bayesian Pseudocoresets
Polynomial-Time Optimal Equilibria with a Mediator in Extensive-Form Games
Bandit Learning in Concave N-Person Games
Flexible neural representation for physics prediction
Message Passing for Max-weight Independent Set
Countering Feedback Delays in Multi-Agent Learning
Improving Context-Aware Preference Modeling for Language Models
Hierarchical Hybrid Sliced Wasserstein: A Scalable Metric for Heterogeneous Joint Distributions
Online Structure Learning for Feed-Forward and Recurrent Sum-Product Networks
AlphaTablets: A Generic Plane Representation for 3D Planar Reconstruction from Monocular Videos
Laterally Interconnected Self-Organizing Maps in Hand-Written Digit Recognition
VICE: Variational Interpretable Concept Embeddings
MAtt: A Manifold Attention Network for EEG Decoding
Orientation, Scale, and Discontinuity as Emergent Properties of Illusory Contour Shape
A Robust Phased Elimination Algorithm for Corruption-Tolerant Gaussian Process Bandits
A New Family of Generalization Bounds Using Samplewise Evaluated CMI
Diffusion Maps, Spectral Clustering and Eigenfunctions of Fokker-Planck Operators
Bridging Gaps: Federated Multi-View Clustering in Heterogeneous Hybrid Views
M 2 SODAI: Multi-Modal Maritime Object Detection Dataset With RGB and Hyperspectral Image Sensors
Evaluating Multiview Object Consistency in Humans and Image Models
Understanding and Minimising Outlier Features in Transformer Training
Coordinated Proximal Policy Optimization
Agnostic Selective Classification
DreamClear: High-Capacity Real-World Image Restoration with Privacy-Safe Dataset Curation
Computing the Stationary Distribution Locally
Modeling Time Varying Systems Using Hidden Control Neural Architecture
Task-Free Continual Learning via Online Discrepancy Distance Learning
Statistical Active Learning Algorithms
Input Reconstruction Reliability Estimation
Fast Gaussian Process Regression using KD-Trees
DevFly: Bio-Inspired Development of Binary Connections for Locality Preserving Sparse Codes
Lending Interaction Wings to Recommender Systems with Conversational Agents
Unitary Convolutions for Learning on Graphs and Groups
Adversarial Attack Generation Empowered by Min-Max Optimization
Cross-Spectral Factor Analysis
Plasticity Kernels and Temporal Statistics
Synergies between Intrinsic and Synaptic Plasticity in Individual Model Neurons
Self-Adaptable Point Processes with Nonparametric Time Decays
Gene Expression Clustering with Functional Mixture Models
Random Features for Large-Scale Kernel Machines
Transformers Represent Belief State Geometry in their Residual Stream
Understanding the Failure of Batch Normalization for Transformers in NLP
RandNet-Parareal: a time-parallel PDE solver using Random Neural Networks
Addressing Negative Transfer in Diffusion Models
A Self-Organizing Multiple-View Representations of 3D Objects
Learning spatiotemporal piecewise-geodesic trajectories from longitudinal manifold-valued data
Connection Topology and Dynamics in Lateral Inhibition Networks
Cost-Sensitive Self-Training for Optimizing Non-Decomposable Metrics
Efficient Model-Free Exploration in Low-Rank MDPs
On Learning Multi-Modal Forgery Representation for Diffusion Generated Video Detection
Buffer of Thoughts: Thought-Augmented Reasoning with Large Language Models
TaylorGAN: Neighbor-Augmented Policy Update Towards Sample-Efficient Natural Language Generation
When False Positive is Intolerant: End-to-End Optimization with Low FPR for Multipartite Ranking
Learning the Linear Quadratic Regulator from Nonlinear Observations
Proximity Graphs for Clustering and Manifold Learning
FishNet: A Versatile Backbone for Image, Region, and Pixel Level Prediction
Persistence Fisher Kernel: A Riemannian Manifold Kernel for Persistence Diagrams
Adaptive Elastic Input Field for Recognition Improvement
Rethinking the Membrane Dynamics and Optimization Objectives of Spiking Neural Networks
Multilayer Neural Networks: One or Two Hidden Layers?
Online Corrupted User Detection and Regret Minimization
Correlation Aware Sparsified Mean Estimation Using Random Projection
Limitations of Lazy Training of Two-layers Neural Network
Distributionally Robust Optimization via Ball Oracle Acceleration
Parameter Competition Balancing for Model Merging
Improved Dropout for Shallow and Deep Learning
Picking on the Same Person: Does Algorithmic Monoculture lead to Outcome Homogenization?
Online convex optimization for cumulative constraints
On Local Rewards and Scaling Distributed Reinforcement Learning
Model Selection for Contextual Bandits
Soft ascent-descent as a stable and flexible alternative to flooding
MedSat: A Public Health Dataset for England Featuring Medical Prescriptions and Satellite Imagery
PACE: Marrying generalization in PArameter-efficient fine-tuning with Consistency rEgularization
Reflection methods for user-friendly submodular optimization
Leveraging Environment Interaction for Automated PDDL Translation and Planning with Large Language Models
Improving Transformer with an Admixture of Attention Heads
Unsupervised Template Learning for Fine-Grained Object Recognition
Learning Preferences for Multiclass Problems
Representation and Induction of Finite State Machines using Time-Delay Neural Networks
Data Acquisition via Experimental Design for Data Markets
Interpreting Images by Propagating Bayesian Beliefs
Seeing through water
Personalized Benchmarking with the Ludwig Benchmarking Toolkit
DrivingDojo Dataset: Advancing Interactive and Knowledge-Enriched Driving World Model
Preventing Gradient Attenuation in Lipschitz Constrained Convolutional Networks
Bayesian Regularization and Nonnegative Deconvolution for Time Delay Estimation
Optimal Sparse Linear Encoders and Sparse PCA
Counterfactual Fairness with Partially Known Causal Graph
Private Synthetic Data for Multitask Learning and Marginal Queries
Good Semi-supervised Learning That Requires a Bad GAN
Mismatch String Kernels for SVM Protein Classification
Reinforcement Learning for Fine-tuning Text-to-Image Diffusion Models
Guarantees for Self-Play in Multiplayer Games via Polymatrix Decomposability
End-to-end reconstruction meets data-driven regularization for inverse problems
Neural Network Visualization
Towards Gradient-based Bilevel Optimization with Non-convex Followers and Beyond
Gaussian Process Conditional Copulas with Applications to Financial Time Series
Tensor Normal Training for Deep Learning Models
Confidence Intervals for the Area Under the ROC Curve
TopoFR: A Closer Look at Topology Alignment on Face Recognition
Job-SDF: A Multi-Granularity Dataset for Job Skill Demand Forecasting and Benchmarking
Walking in the Shadow: A New Perspective on Descent Directions for Constrained Minimization
Multiclass Learning with Simplex Coding
beta-risk: a New Surrogate Risk for Learning from Weakly Labeled Data
System Identification with Biophysical Constraints: A Circuit Model of the Inner Retina
Combinatorial Structures and Processing in Neural Blackboard Architectures
Sample Complexity of Learning Heuristic Functions for Greedy-Best-First and A* Search
How to talk so AI will learn: Instructions, descriptions, and autonomy
On the equivalence between graph isomorphism testing and function approximation with GNNs
Semantic Density: Uncertainty Quantification for Large Language Models through Confidence Measurement in Semantic Space
Logarithmic Regret Bound in Partially Observable Linear Dynamical Systems
Balanced Policy Evaluation and Learning
COCO-Counterfactuals: Automatically Constructed Counterfactual Examples for Image-Text Pairs
Policy Gradient for Coherent Risk Measures
Support Recovery in Sparse PCA with Incomplete Data
The Value of Labeled and Unlabeled Examples when the Model is Imperfect
Binary to Bushy: Bayesian Hierarchical Clustering with the Beta Coalescent
Prototypical Variational Autoencoder for 3D Few-shot Object Detection
Empowering Active Learning for 3D Molecular Graphs with Geometric Graph Isomorphism
Staircase Attention for Recurrent Processing of Sequences
Human Memory Search as Initial-Visit Emitting Random Walk
Parametric Simplex Method for Sparse Learning
Enhancing Large Vision Language Models with Self-Training on Image Comprehension
Customized Multiple Clustering via Multi-Modal Subspace Proxy Learning
Detecting Moments and Highlights in Videos via Natural Language Queries
Estimating Spatial Layout of Rooms using Volumetric Reasoning about Objects and Surfaces
Reinforcement Learning Enhanced Explainer for Graph Neural Networks
Environment-Aware Dynamic Graph Learning for Out-of-Distribution Generalization
Data Minimization at Inference Time
Dispelling the Mirage of Progress in Offline MARL through Standardised Baselines and Evaluation
Real-Time Decoding of an Integrate and Fire Encoder
Efficient and Flexible Inference for Stochastic Systems
LM-HT SNN: Enhancing the Performance of SNN to ANN Counterpart through Learnable Multi-hierarchical Threshold Model
Neural Production Systems
Recognizing retinal ganglion cells in the dark
Learning Audio-Visual Dynamics Using Scene Graphs for Audio Source Separation
Best Arm Identification in Contaminated Stochastic Bandits
Human-AI Shared Control via Policy Dissection
Combining Behaviors with the Successor Features Keyboard
Stabilizing Value Function Approximation with the BFBP Algorithm
Orthogonally Decoupled Variational Gaussian Processes
AsyncDiff: Parallelizing Diffusion Models by Asynchronous Denoising
Self-Distillation Amplifies Regularization in Hilbert Space
DOFEN: Deep Oblivious Forest ENsemble
Bayesian Active Causal Discovery with Multi-Fidelity Experiments
Analog Neural Networks as Decoders
Belief Projection-Based Reinforcement Learning for Environments with Delayed Feedback
TANGO: Text-driven Photorealistic and Robust 3D Stylization via Lighting Decomposition
A Connectionist Learning Control Architecture for Navigation
Learning Many Related Tasks at the Same Time with Backpropagation
Multi-Robot Negotiation: Approximating the Set of Subgame Perfect Equilibria in General-Sum Stochastic Games
The balancing principle for parameter choice in distance-regularized domain adaptation
Aligning Gradient and Hessian for Neural Signed Distance Function
Efficient Minimization of Decomposable Submodular Functions
Efficient inference for time-varying behavior during learning
cpSGD: Communication-efficient and differentially-private distributed SGD
Adaptive optimal training of animal behavior
Provable Guarantees for Generative Behavior Cloning: Bridging Low-Level Stability and High-Level Behavior
Fast Minimum-norm Adversarial Attacks through Adaptive Norm Constraints
Noisy Spiking Neurons with Temporal Coding have more Computational Power than Sigmoidal Neurons
Efficiency versus Convergence of Boolean Kernels for On-Line Learning Algorithms
Hierarchical Lattice Layer for Partially Monotone Neural Networks
Similarity by Composition
Multi-Facet Clustering Variational Autoencoders
Graphon Neural Networks and the Transferability of Graph Neural Networks
A Bayesian Perspective on Training Speed and Model Selection
Honor Among Bandits: No-Regret Learning for Online Fair Division
Approximately Pareto-optimal Solutions for Bi-Objective k-Clustering
Cal-DPO: Calibrated Direct Preference Optimization for Language Model Alignment
Bayesian Pedigree Analysis using Measure Factorization
No-Regret Learning with Unbounded Losses: The Case of Logarithmic Pooling
On the consistency theory of high dimensional variable screening
FlyView: a bio-informed optical flow truth dataset for visual navigation using panoramic stereo vision
Estimating Average-Case Learning Curves Using Bayesian, Statistical Physics and VC Dimension Methods
GTM: A Principled Alternative to the Self-Organizing Map
Deep Structured Prediction for Facial Landmark Detection
Imitating Language via Scalable Inverse Reinforcement Learning
Knowledge-Augmented Reasoning Distillation for Small Language Models in Knowledge-Intensive Tasks
DMesh: A Differentiable Mesh Representation
Unveiling LoRA Intrinsic Ranks via Salience Analysis
Trait Selection for Assessing Beef Meat Quality Using Non-linear SVM
Distributional Pareto-Optimal Multi-Objective Reinforcement Learning
Adaptive Reduced Rank Regression
Integrating Suboptimal Human Knowledge with Hierarchical Reinforcement Learning for Large-Scale Multiagent Systems
Scalable Inference in SDEs by Direct Matching of the Fokker-Planck-Kolmogorov Equation
Learning to Discover Skills through Guidance
Generative Visual Prompt: Unifying Distributional Control of Pre-Trained Generative Models
Detecting Significant Multidimensional Spatial Clusters
Self-Organizing Rules for Robust Principal Component Analysis
Learning Strategy-Aware Linear Classifiers
Stabilized Proximal-Point Methods for Federated Optimization
Effective Dimension and Generalization of Kernel Learning
Diversity-Guided Multi-Objective Bayesian Optimization With Batch Evaluations
On Calibrating Diffusion Probabilistic Models
Large Scale Transfer Learning for Tabular Data via Language Modeling
Frequency-Domain Dynamic Pruning for Convolutional Neural Networks
The Power of Amnesia
Real Time Voice Processing with Audiovisual Feedback: Toward Autonomous Agents with Perfect Pitch
Reorganisation of Somatosensory Cortex after Tactile Training
QUEST: Quality-Aware Metropolis-Hastings Sampling for Machine Translation
Robust Bayesian Max-Margin Clustering
Towards Robust Blind Face Restoration with Codebook Lookup Transformer
CityRefer: Geography-aware 3D Visual Grounding Dataset on City-scale Point Cloud Data
On Weak Regret Analysis for Dueling Bandits
Forethought and Hindsight in Credit Assignment
Recurrent Cortical Competition: Strengthen or Weaken?
FreqBlender: Enhancing DeepFake Detection by Blending Frequency Knowledge
HiRID-ICU-Benchmark - A Comprehensive Machine Learning Benchmark on High-resolution ICU Data
Implementing Intelligence on Silicon Using Neuron-Like Functional MOS Transistors
Top-k Multiclass SVM
Data Portraits: Recording Foundation Model Training Data
Physics-Driven ML-Based Modelling for Correcting Inverse Estimation
Greedy Optimization Provably Wins the Lottery: Logarithmic Number of Winning Tickets is Enough
Retrospective Analysis of the 2019 MineRL Competition on Sample Efficient Reinforcement Learning
Neural Injective Functions for Multisets, Measures and Graphs via a Finite Witness Theorem
LambdaBeam: Neural Program Search with Higher-Order Functions and Lambdas
Learning Neural Network Policies with Guided Policy Search under Unknown Dynamics
Fast Bayesian Inference with Batch Bayesian Quadrature via Kernel Recombination
ASSANet: An Anisotropic Separable Set Abstraction for Efficient Point Cloud Representation Learning
Temporal and Cross-Subject Probabilistic Models for fMRI Prediction Tasks
Fractal Patterns May Illuminate the Success of Next-Token Prediction
Differentiable Expected Hypervolume Improvement for Parallel Multi-Objective Bayesian Optimization
D-MiSo: Editing Dynamic 3D Scenes using Multi-Gaussians Soup
ResNEsts and DenseNEsts: Block-based DNN Models with Improved Representation Guarantees
A Phase Transition between Positional and Semantic Learning in a Solvable Model of Dot-Product Attention
Scaling of Probability-Based Optimization Algorithms
A Mean Field Theory of Layer IV of Visual Cortex and Its Application to Artificial Neural Networks
Solving Large Sequential Games with the Excessive Gap Technique
NetHack is Hard to Hack
ProTo: Program-Guided Transformer for Program-Guided Tasks
M 4 : A Unified XAI Benchmark for Faithfulness Evaluation of Feature Attribution Methods across Metrics, Modalities and Models
NeurIPS 2019 Competition and Demonstration Track, 8-14 December 2019, Vancouver, Canada. Revised selected papers
SwiftSage: A Generative Agent with Fast and Slow Thinking for Complex Interactive Tasks
Gaussian Processes for Survival Analysis
Synthetic Data Generators - Sequential and Private
Large Margin Taxonomy Embedding for Document Categorization
De-randomizing MCMC dynamics with the diffusion Stein operator
Confidence Calibration of Classifiers with Many Classes
A Unified Analysis of Mixed Sample Data Augmentation: A Loss Function Perspective
A One-Size-Fits-All Approach to Improving Randomness in Paper Assignment
TorchSpatial: A Location Encoding Framework and Benchmark for Spatial Representation Learning
Learning to Learn Dense Gaussian Processes for Few-Shot Learning
Improved Regret Bounds for Tracking Experts with Memory
LLMCBench: Benchmarking Large Language Model Compression for Efficient Deployment
If You Want to Be Robust, Be Wary of Initialization
An Efficient Memory Module for Graph Few-Shot Class-Incremental Learning
Sex with Support Vector Machines
Discriminative Feature Attributions: Bridging Post Hoc Explainability and Inherent Interpretability
Learning in Congestion Games with Bandit Feedback
Accelerated Projected Gradient Algorithms for Sparsity Constrained Optimization Problems
Neural Set Function Extensions: Learning with Discrete Functions in High Dimensions
Simple random search of static linear policies is competitive for reinforcement learning
$\text{Di}^2\text{Pose}$: Discrete Diffusion Model for Occluded 3D Human Pose Estimation
GemNet: Universal Directional Graph Neural Networks for Molecules
The variational hierarchical EM algorithm for clustering hidden Markov models
Fast and Provable ADMM for Learning with Generative Priors
Guided Trajectory Generation with Diffusion Models for Offline Model-based Optimization
Classic GNNs are Strong Baselines: Reassessing GNNs for Node Classification
Nonlinear causal discovery with additive noise models
Temporal Positive-unlabeled Learning for Biomedical Hypothesis Generation via Risk Estimation
Low-Rank Extragradient Method for Nonsmooth and Low-Rank Matrix Optimization Problems
LiRo: Benchmark and leaderboard for Romanian language tasks
Pure Transformers are Powerful Graph Learners
Continual Learning with Node-Importance based Adaptive Group Sparse Regularization
Tight last-iterate convergence rates for no-regret learning in multi-player games
Sample-efficient Bayesian Optimisation Using Known Invariances
Energy-based Epistemic Uncertainty for Graph Neural Networks
Locality defeats the curse of dimensionality in convolutional teacher-student scenarios
Reducing statistical time-series problems to binary classification
Gaussian Process Prior Variational Autoencoders
LoD-Loc: Aerial Visual Localization using LoD 3D Map with Neural Wireframe Alignment
Deep Neural Networks Segment Neuronal Membranes in Electron Microscopy Images
Online Sum-Product Computation Over Trees
Multi-task Gaussian Process Prediction
An Object-Oriented Framework for the Simulation of Neural Networks
Iterative Causal Discovery in the Possible Presence of Latent Confounders and Selection Bias
Support Vector Machines on a Budget
Locally Private Learning without Interaction Requires Separation
Digital-Analog Hybrid Synapse Chips for Electronic Neural Networks
Generalization Error Bounds for Aggregation by Mirror Descent with Averaging
Nearest Neighbor based Greedy Coordinate Descent
PatchComplete: Learning Multi-Resolution Patch Priors for 3D Shape Completion on Unseen Categories
On the Sample Complexity of Privately Learning Axis-Aligned Rectangles
Tempering Backpropagation Networks: Not All Weights are Created Equal
Mixture of Demonstrations for In-Context Learning
Conditional Score Guidance for Text-Driven Image-to-Image Translation
Are Defenses for Graph Neural Networks Robust?
Rethinking Model-based, Policy-based, and Value-based Reinforcement Learning via the Lens of Representation Complexity
Generalized Bayesian Inference for Scientific Simulators via Amortized Cost Estimation
A biologically plausible network for the computation of orientation dominance
Neural Pseudo-Label Optimism for the Bank Loan Problem
A 1, 000-Neuron System with One Million 7-bit Physical Interconnections
Density estimation from unweighted k-nearest neighbor graphs: a roadmap
Structure Driven Image Database Retrieval
Practical and Asymptotically Exact Conditional Sampling in Diffusion Models
Flexible Models for Microclustering with Application to Entity Resolution
Deep Attentive Tracking via Reciprocative Learning
The Pareto Regret Frontier
Probabilistic Circuits for Variational Inference in Discrete Graphical Models
Hydra: Bidirectional State Space Models Through Generalized Matrix Mixers
SPANN: Highly-efficient Billion-scale Approximate Nearest Neighborhood Search
Deep active inference agents using Monte-Carlo methods
Semi-supervised Learning with Ladder Networks
Optimal prior-dependent neural population codes under shared input noise
Active Labeling: Streaming Stochastic Gradients
The PRISM Alignment Dataset: What Participatory, Representative and Individualised Human Feedback Reveals About the Subjective and Multicultural Alignment of Large Language Models
Leverage the Average: an Analysis of KL Regularization in Reinforcement Learning
Value Pursuit Iteration
Spectral Learning of Large Structured HMMs for Comparative Epigenomics
Breaking Semantic Artifacts for Generalized AI-generated Image Detection
Explicit Eigenvalue Regularization Improves Sharpness-Aware Minimization
MM-Fi: Multi-Modal Non-Intrusive 4D Human Dataset for Versatile Wireless Sensing
Micro-Bench: A Microscopy Benchmark for Vision-Language Understanding
Contour location via entropy reduction leveraging multiple information sources
Generalizing Bayesian Optimization with Decision-theoretic Entropies