yusuke1997/dblp-id-title huggingface dataset:
Learning Disentangled Representations for Perceptual Point Cloud Quality Assessment via Mutual Information Minimization
Learning State Representations from Random Deep Action-conditional Predictions
Efficient Partial Monitoring with Prior Information
Continuous Doubly Constrained Batch Reinforcement Learning
Function-Space Distributions over Kernels
Topological Obstructions and How to Avoid Them
Predicting Weather Using a Genetic Memory: A Combination of Kanerva's Sparse Distributed Memory with Holland's Genetic Algorithms
Breaking Long-Tailed Learning Bottlenecks: A Controllable Paradigm with Hypernetwork-Generated Diverse Experts
Lipreading by Neural Networks: Visual Preprocessing, Learning, and Sensory Integration
Online Control of Unknown Time-Varying Dynamical Systems
Stability and Generalization of Asynchronous SGD: Sharper Bounds Beyond Lipschitz and Smoothness
Nonlinear Acceleration of Stochastic Algorithms
Are deep ResNets provably better than linear predictors?
On the Use of Evidence in Neural Networks
Towards Accelerated Model Training via Bayesian Data Selection
Facilitating Multimodal Classification via Dynamically Learning Modality Gap
Online Continuous Submodular Maximization: From Full-Information to Bandit Feedback
Confidence Sets for Network Structure
Leveraging Factored Action Spaces for Efficient Offline Reinforcement Learning in Healthcare
Getting lost in space: Large sample analysis of the resistance distance
Motif-based Graph Self-Supervised Learning for Molecular Property Prediction
Boosted Conformal Prediction Intervals
Instruction Tuning With Loss Over Instructions
Efficient and Accurate Gradients for Neural SDEs
Subspace Clustering with Irrelevant Features via Robust Dantzig Selector
The Blinded Bandit: Learning with Adaptive Feedback
ARC: A Generalist Graph Anomaly Detector with In-Context Learning
Normalization Layers Are All That Sharpness-Aware Minimization Needs
Learning to Find Pre-Images
Module-wise Adaptive Distillation for Multimodality Foundation Models
Stochastic Relational Models for Large-scale Dyadic Data using MCMC
What Makes for Good Views for Contrastive Learning?
Learning Structured Output Representation using Deep Conditional Generative Models
Learning curves of generic features maps for realistic datasets with a teacher-student model
Multi-task learning with summary statistics
Modeling User Rating Profiles For Collaborative Filtering
Lifelong Policy Gradient Learning of Factored Policies for Faster Training Without Forgetting
Simplifying Neural Nets by Discovering Flat Minima
Discretely Relaxing Continuous Variables for tractable Variational Inference
DiffuBox: Refining 3D Object Detection with Point Diffusion
On Differentially Private Subspace Estimation in a Distribution-Free Setting
Relative Density Nets: A New Way to Combine Backpropagation with HMM's
Identifying Causal-Effect Inference Failure with Uncertainty-Aware Models
Structure Consistent Gaussian Splatting with Matching Prior for Few-shot Novel View Synthesis
Approximate Dynamic Programming via Linear Programming
Spatio-Temporal Variational Gaussian Processes
Generic Neural Architecture Search via Regression
Data Diversification: A Simple Strategy For Neural Machine Translation
The SpaceNet Multi-Temporal Urban Development Challenge
Legendre Decomposition for Tensors
Matrix factorization with binary components
Learning Tree Structured Potential Games
Fine-Tuning is Fine, if Calibrated
Functional Adversarial Attacks
FinCon: A Synthesized LLM Multi-Agent System with Conceptual Verbal Reinforcement for Enhanced Financial Decision Making
Programmable Analog Pulse-Firing Neural Networks
Bayesian latent structure discovery from multi-neuron recordings
Adversarial Learning for Robust Deep Clustering
Online Label Shift: Optimal Dynamic Regret meets Practical Algorithms
A Simple yet Scalable Granger Causal Structural Learning Approach for Topological Event Sequences
Robust $\phi$-Divergence MDPs
Limiting Form of the Sample Covariance Eigenspectrum in PCA and Kernel PCA
Listen to Interpret: Post-hoc Interpretability for Audio Networks with NMF
Unsupervised Depth Estimation, 3D Face Rotation and Replacement
Bandit-Feedback Online Multiclass Classification: Variants and Tradeoffs
Trading Bitcoin and Online Time Series Prediction
Randomized Channel Shuffling: Minimal-Overhead Backdoor Attack Detection without Clean Datasets
Heterogeneous Component Analysis
In-Context Learning with Representations: Contextual Generalization of Trained Transformers
Learning in Spiking Neural Assemblies
TAAC: Temporally Abstract Actor-Critic for Continuous Control
A General and Efficient Multiple Kernel Learning Algorithm
A Network Mechanism for the Determination of Shape-from-Texture
Codec Avatar Studio: Paired Human Captures for Complete, Driveable, and Generalizable Avatars
Expectation-Maximization Contrastive Learning for Compact Video-and-Language Representations
What Makes Multi-Modal Learning Better than Single (Provably)
Comparing Causal Frameworks: Potential Outcomes, Structural Models, Graphs, and Abstractions
Learning from Observation-Only Demonstration for Task-Oriented Language Grounding via Self-Examination
Flare7K: A Phenomenological Nighttime Flare Removal Dataset
Hierarchical Modeling of Local Image Features through $L_p$-Nested Symmetric Distributions
Exponentially convergent stochastic k-PCA without variance reduction
Actor-Critic Algorithms
Risk-Sensitive Reinforcement Learning: Near-Optimal Risk-Sample Tradeoff in Regret
MiliPoint: A Point Cloud Dataset for mmWave Radar
Generalization Properties of Radial Basis Functions
HONOR: Hybrid Optimization for NOn-convex Regularized problems
Online Learning and Control of Complex Dynamical Systems from Sensory Input
Regret Minimization in Games with Incomplete Information
Demystifying the Optimal Performance of Multi-Class Classification
Unbiased Classification through Bias-Contrastive and Bias-Balanced Learning
An analysis of Ermakov-Zolotukhin quadrature using kernels
Polar Operators for Structured Sparse Estimation
Pseudo-Siamese Blind-spot Transformers for Self-Supervised Real-World Denoising
Transformer-based Planning for Symbolic Regression
Dirichlet Energy Constrained Learning for Deep Graph Neural Networks
Towards Instance-Optimal Offline Reinforcement Learning with Pessimism
Unsupervised Parallel Feature Extraction from First Principles
Learning Cellular Automation Dynamics with Neural Networks
Few-shot Generation via Recalling Brain-Inspired Episodic-Semantic Memory
Adversarial Multiclass Classification: A Risk Minimization Perspective
Lasso Screening Rules via Dual Polytope Projection
Iterative Double Clustering for Unsupervised and Semi-Supervised Learning
Graph Neural Networks with Local Graph Parameters
Saliency, Scale and Information: Towards a Unifying Theory
Multitask Spectral Learning of Weighted Automata
CLIPLoss and Norm-Based Data Selection Methods for Multimodal Contrastive Learning
Strongly local p-norm-cut algorithms for semi-supervised learning and local graph clustering
Outlier-Robust Sparse Mean Estimation for Heavy-Tailed Distributions
Distribution Learning of a Random Spatial Field with a Location-Unaware Mobile Sensor
Contextual bandits with surrogate losses: Margin bounds and efficient algorithms
ErrorCompensatedX: error compensation for variance reduced algorithms
An $\alpha$-No-Regret Algorithm For Graphical Bilinear Bandits
emg2pose: A Large and Diverse Benchmark for Surface Electromyographic Hand Pose Estimation
TD Convergence: An Optimization Perspective
Submodular Function Minimization with Noisy Evaluation Oracle
Stable LInear Approximations to Dynamic Programming for Stochastic Control Problems with Local Transitions
Intrinsic Dimension Estimation for Robust Detection of AI-Generated Texts
Semi-Supervised Semantic Segmentation via Adaptive Equalization Learning
StepbaQ: Stepping backward as Correction for Quantized Diffusion Models
Monte Carlo Value Iteration with Macro-Actions
SemMAE: Semantic-Guided Masking for Learning Masked Autoencoders
Profile Entropy: A Fundamental Measure for the Learnability and Compressibility of Distributions
Dirichlet-Bernoulli Alignment: A Generative Model for Multi-Class Multi-Label Multi-Instance Corpora
Why Generalization in RL is Difficult: Epistemic POMDPs and Implicit Partial Observability
Active Ranking using Pairwise Comparisons
Riemannian Projection-free Online Learning
Beyond Actions: Discriminative Models for Contextual Group Activities
DynPoint: Dynamic Neural Point For View Synthesis
Learning to Propagate for Graph Meta-Learning
Quantum Deep Equilibrium Models
NIS3D: A Completely Annotated Benchmark for Dense 3D Nuclei Image Segmentation
Computing Optimal Nash Equilibria in Multiplayer Games
Optimal Binary Classifier Aggregation for General Losses
Learning the Structure of Large Networked Systems Obeying Conservation Laws
SciGen: a Dataset for Reasoning-Aware Text Generation from Scientific Tables
Hierarchical Decomposition of Prompt-Based Continual Learning: Rethinking Obscured Sub-optimality
Understanding, Predicting and Better Resolving Q-Value Divergence in Offline-RL
FineStyle: Fine-grained Controllable Style Personalization for Text-to-image Models
Robot Docking Using Mixtures of Gaussians
Zeroth-Order Stochastic Variance Reduction for Nonconvex Optimization
Exploiting Syllable Structure in a Connectionist Phonology Model
A Representation Theory for Ranking Functions
Unexpected Improvements to Expected Improvement for Bayesian Optimization
Déjà Vu Memorization in Vision-Language Models
An In-depth Study of Stochastic Backpropagation
A Note on Learning Vector Quantization
PRED: Pre-training via Semantic Rendering on LiDAR Point Clouds
Decoupling the Depth and Scope of Graph Neural Networks
Mathematical Analysis of Learning Behavior of Neuronal Models
On Multiplicative Integration with Recurrent Neural Networks
Statistical mechanics of low-rank tensor decomposition
Truncated Variance Reduced Value Iteration
Off-Policy Evaluation for Episodic Partially Observable Markov Decision Processes under Non-Parametric Models
Constant Approximation for Individual Preference Stable Clustering
When to use parametric models in reinforcement learning?
Logarithmic-Regret Quantum Learning Algorithms for Zero-Sum Games
UGC: Universal Graph Coarsening
Transformers Generalize DeepSets and Can be Extended to Graphs & Hypergraphs
Exploring Figure-Ground Assignment Mechanism in Perceptual Organization
Joint Contrastive Learning with Infinite Possibilities
FR: Folded Rationalization with a Unified Encoder
A Hierarchical Reinforcement Learning Based Optimization Framework for Large-scale Dynamic Pickup and Delivery Problems
One-Sided Unsupervised Domain Mapping
Minimax Estimation of Bandable Precision Matrices
Learning to Prune in Metric and Non-Metric Spaces
Kernel Bayesian Inference with Posterior Regularization
Task-recency bias strikes back: Adapting covariances in Exemplar-Free Class Incremental Learning
Masked Hard-Attention Transformers Recognize Exactly the Star-Free Languages
SyncTwin: Treatment Effect Estimation with Longitudinal Outcomes
A Nonlinear Predictive State Representation
T2I-CompBench: A Comprehensive Benchmark for Open-world Compositional Text-to-image Generation
Sparse Coding for Learning Interpretable Spatio-Temporal Primitives
Unlocking the Potential of Global Human Expertise
Using Options and Covariance Testing for Long Horizon Off-Policy Policy Evaluation
Black-Box Certification with Randomized Smoothing: A Functional Optimization Based Framework
Conservative State Value Estimation for Offline Reinforcement Learning
Hardware Conditioned Policies for Multi-Robot Transfer Learning
SizeShiftReg: a Regularization Method for Improving Size-Generalization in Graph Neural Networks
SituatedGen: Incorporating Geographical and Temporal Contexts into Generative Commonsense Reasoning
Dirty Statistical Models
UWSOD: Toward Fully-Supervised-Level Capacity Weakly Supervised Object Detection
Balancing Efficiency and Fairness in On-Demand Ridesourcing
STONE: A Submodular Optimization Framework for Active 3D Object Detection
FUSU: A Multi-temporal-source Land Use Change Segmentation Dataset for Fine-grained Urban Semantic Understanding
Integration-free Training for Spatio-temporal Multimodal Covariate Deep Kernel Point Processes
Direct Runge-Kutta Discretization Achieves Acceleration
Follow-ups Also Matter: Improving Contextual Bandits via Post-serving Contexts
Pretrained Transformer Efficiently Learns Low-Dimensional Target Functions In-Context
PDF: Point Diffusion Implicit Function for Large-scale Scene Neural Representation
Bayesian target optimisation for high-precision holographic optogenetics
A Direct Approximation of AIXI Using Logical State Abstractions
The Infinite Factorial Hidden Markov Model
Weight decay induces low-rank attention layers
Monte Carlo Augmented Actor-Critic for Sparse Reward Deep Reinforcement Learning from Suboptimal Demonstrations
Visual Concept-Metaconcept Learning
Efficient Recurrent Off-Policy RL Requires a Context-Encoder-Specific Learning Rate
Group Equivariant Subsampling
Can Peripheral Representations Improve Clutter Metrics on Complex Scenes?
AV-GS: Learning Material and Geometry Aware Priors for Novel View Acoustic Synthesis
Probability Paths and the Structure of Predictions over Time
Low Power Wireless Communication via Reinforcement Learning
EDGE: Explaining Deep Reinforcement Learning Policies
PointAD: Comprehending 3D Anomalies from Points and Pixels for Zero-shot 3D Anomaly Detection
On Semi-Supervised Classification
Can contrastive learning avoid shortcut solutions?
Guaranteed Rank Minimization via Singular Value Projection
Hyperparameter Learning for Graph Based Semi-supervised Learning Algorithms
An Online Sequence-to-Sequence Model Using Partial Conditioning
Self-Tuning Spectral Clustering
Enhancing Graph Transformers with Hierarchical Distance Structural Encoding
GAN You See Me? Enhanced Data Reconstruction Attacks against Split Inference
The Reliability of OKRidge Method in Solving Sparse Ridge Regression Problems
Reconstruction Attacks on Machine Unlearning: Simple Models are Vulnerable
Semi-Supervised Learning with Declaratively Specified Entropy Constraints
Bayesian Agglomerative Clustering with Coalescents
Convergence of Adversarial Training in Overparametrized Neural Networks
Learning Robust Dynamics through Variational Sparse Gating
Convex Clustering with Exemplar-Based Models
Relative Performance Guarantees for Approximate Inference in Latent Dirichlet Allocation
A Synthetic Dataset for Personal Attribute Inference
Guide Your Agent with Adaptive Multimodal Rewards
Learning Retrospective Knowledge with Reverse Reinforcement Learning
Regression with Input-dependent Noise: A Gaussian Process Treatment
Happy: A Debiased Learning Framework for Continual Generalized Category Discovery
Two Heads are Better Than One: A Simple Exploration Framework for Efficient Multi-Agent Reinforcement Learning
Agreement-on-the-line: Predicting the Performance of Neural Networks under Distribution Shift
Protected Test-Time Adaptation via Online Entropy Matching: A Betting Approach
Temporal Representations in a Connectionist Speech System
Stronger Than You Think: Benchmarking Weak Supervision on Realistic Tasks
Convergence of Optimistic and Incremental Q-Learning
Maximization of Average Precision for Deep Learning with Adversarial Ranking Robustness
The Discrete Gaussian for Differential Privacy
Eye movements and the maturation of cortical orientation selectivity
Exploration Bonus for Regret Minimization in Discrete and Continuous Average Reward MDPs
Neural Fields with Hard Constraints of Arbitrary Differential Order
S 3 : Increasing GPU Utilization during Generative Inference for Higher Throughput
Smoothed Gradients for Stochastic Variational Inference
The Machine Learning for Combinatorial Optimization Competition (ML4CO): Results and Insights
Efficient Bayesian Inference for Dynamically Changing Graphs
Cross-Episodic Curriculum for Transformer Agents
Monte Carlo Tree Search With Iteratively Refining State Abstractions
On Evaluating Adversarial Robustness of Large Vision-Language Models
NoMAD-Attention: Efficient LLM Inference on CPUs Through Multiply-add-free Attention
EffiLearner: Enhancing Efficiency of Generated Code via Self-Optimization
Norepinephrine and Neural Interrupts
MiniCache: KV Cache Compression in Depth Dimension for Large Language Models
Human Reading and the Curse of Dimensionality
Conformal Bayesian Computation
Generalized test utilities for long-tail performance in extreme multi-label classification
Real-Time Monitoring of Complex Industrial Processes with Particle Filters
Physiologically Based Speech Synthesis
Text Promptable Surgical Instrument Segmentation with Vision-Language Models
Touchstone Benchmark: Are We on the Right Way for Evaluating AI Algorithms for Medical Segmentation?
Accountability in Offline Reinforcement Learning: Explaining Decisions with a Corpus of Examples
GAIA: Rethinking Action Quality Assessment for AI-Generated Videos
Managing Temporal Resolution in Continuous Value Estimation: A Fundamental Trade-off
Data curation via joint example selection further accelerates multimodal learning
A Faster Maximum Cardinality Matching Algorithm with Applications in Machine Learning
Weakly-Supervised Concealed Object Segmentation with SAM-based Pseudo Labeling and Multi-scale Feature Grouping
FairWire: Fair Graph Generation
Learning Optimal Predictive Checklists
L 1 -Penalized Robust Estimation for a Class of Inverse Problems Arising in Multiview Geometry
Nimble: Lightweight and Parallel GPU Task Scheduling for Deep Learning
Simultaneous Object Detection and Ranking with Weak Supervision
Explaining Predictive Uncertainty with Information Theoretic Shapley Values
Learning a Warping Distance from Unlabeled Time Series Using Sequence Autoencoders
Shape And Structure Preserving Differential Privacy
Interesting Object, Curious Agent: Learning Task-Agnostic Exploration
Unsupervised Object Segmentation by Redrawing
A Multi-modal Global Instance Tracking Benchmark (MGIT): Better Locating Target in Complex Spatio-temporal and Causal Relationship
Advantage Updating Applied to a Differrential Game
MATE: Benchmarking Multi-Agent Reinforcement Learning in Distributed Target Coverage Control
A convex optimization formulation for multivariate regression
SAGDA: Achieving $\mathcal{O}(\epsilon^{-2})$ Communication Complexity in Federated Min-Max Learning
Adaptive Learning with Unknown Information Flows
Spatio-Temporal Hilbert Maps for Continuous Occupancy Representation in Dynamic Environments
Anatomically Constrained Decoding of Finger Flexion from Electrocorticographic Signals
VisIT-Bench: A Dynamic Benchmark for Evaluating Instruction-Following Vision-and-Language Models
Exploiting Local Convergence of Quasi-Newton Methods Globally: Adaptive Sample Size Approach
Leveraging Pre-trained Large Language Models to Construct and Utilize World Models for Model-based Task Planning
Learning Semantic Representations to Verify Hardware Designs
SAC: Accelerating and Structuring Self-Attention via Sparse Adaptive Connection
ART2/BP Architecture for Adaptive Estimation of Dynamic Processes
Learning brain regions via large-scale online structured sparse dictionary learning
Efficient and Effective Augmentation Strategy for Adversarial Training
A Deep Learning Dataloader with Shared Data Preparation
Subgrouping Reduces Complexity and Speeds Up Learning in Recurrent Networks
An Analytical Theory of Curriculum Learning in Teacher-Student Networks
Certifying Strategyproof Auction Networks
Efficient Learning of Linear Perceptrons
The Impact of Geometric Complexity on Neural Collapse in Transfer Learning
A Biologically Plausible Algorithm for Reinforcement-shaped Representational Learning
ConvBench: A Multi-Turn Conversation Evaluation Benchmark with Hierarchical Ablation Capability for Large Vision-Language Models
Improved Regret Analysis for Variance-Adaptive Linear Bandits and Horizon-Free Linear Mixture MDPs
An Even More Optimal Stochastic Optimization Algorithm: Minibatching and Interpolation Learning
Optimal kernel choice for large-scale two-sample tests
Towards a general independent subspace analysis
Neurometric function analysis of population codes
Grasp as You Say: Language-guided Dexterous Grasp Generation
Eluder Dimension and the Sample Complexity of Optimistic Exploration
Are GANs overkill for NLP?
Improving the Knowledge Gradient Algorithm
Weak Learners and Improved Rates of Convergence in Boosting
Hybrid Policy Optimization from Imperfect Demonstrations
Kernels for Structured Natural Language Data
A Tensorized Transformer for Language Modeling
Divide-and-Conquer Matrix Factorization
Approximate Dynamic Programming Finally Performs Well in the Game of Tetris
High-Speed Airborne Particle Monitoring Using Artificial Neural Networks
Multilinear Subspace Regression: An Orthogonal Tensor Decomposition Approach
Unpacking DPO and PPO: Disentangling Best Practices for Learning from Preference Feedback
Attractor Memory for Long-Term Time Series Forecasting: A Chaos Perspective
Set-based Neural Network Encoding Without Weight Tying
Efficient Dataset Distillation using Random Feature Approximation
On Sparse Gaussian Chain Graph Models
The Implicit Delta Method
Active Learning in Multilayer Perceptrons
The Curious Price of Distributional Robustness in Reinforcement Learning with a Generative Model
Swarm Reinforcement Learning for Adaptive Mesh Refinement
Rethinking and Reweighting the Univariate Losses for Multi-Label Ranking: Consistency and Generalization
On Path Integration of Grid Cells: Group Representation and Isotropic Scaling
Large Language Models Play StarCraft II: Benchmarks and A Chain of Summarization Approach
Non-reversible Gaussian processes for identifying latent dynamical structure in neural data
Learning from Noisy Labels via Conditional Distributionally Robust Optimization
Bellman Eluder Dimension: New Rich Classes of RL Problems, and Sample-Efficient Algorithms
Adversarial Attacks on Graph Classifiers via Bayesian Optimisation
Zeroth-Order Negative Curvature Finding: Escaping Saddle Points without Gradients
Uncertain Decisions Facilitate Better Preference Learning
Benchmarks for Corruption Invariant Person Re-identification
Visual Interaction Networks: Learning a Physics Simulator from Video
Deep Generative Models for Distribution-Preserving Lossy Compression
Subquadratic Kronecker Regression with Applications to Tensor Decomposition
Deep Bidirectional Language-Knowledge Graph Pretraining
EnvPool: A Highly Parallel Reinforcement Learning Environment Execution Engine
Learning to search efficiently for causally near-optimal treatments
Covariate-Powered Empirical Bayes Estimation
Nonrigid Structure from Motion in Trajectory Space
Federated Linear Bandits with Finite Adversarial Actions
Template-free Articulated Neural Point Clouds for Reposable View Synthesis
Learning Articulated Rigid Body Dynamics with Lagrangian Graph Neural Network
Robust Imitation of Diverse Behaviors
Byzantine Stochastic Gradient Descent
COT-GAN: Generating Sequential Data via Causal Optimal Transport
Robustifying Algorithms of Learning Latent Trees with Vector Variables
A Linearly Convergent Method for Non-Smooth Non-Convex Optimization on the Grassmannian with Applications to Robust Subspace and Dictionary Learning
On the Learnability of Multilabel Ranking
Perfect Associative Learning with Spike-Timing-Dependent Plasticity
Score-based Generative Modeling through Stochastic Evolution Equations in Hilbert Spaces
Pre-training Differentially Private Models with Limited Public Data
Model-Based Imitation Learning for Urban Driving
A Dual Augmented Block Minimization Framework for Learning with Limited Memory
A Polynomial-time Form of Robust Regression
Improved Gaussian Mixture Density Estimates Using Bayesian Penalty Terms and Network Averaging
Retrieve, Reason, and Refine: Generating Accurate and Faithful Patient Instructions
From Bandits to Experts: A Tale of Domination and Independence
Multiclass Boosting: Theory and Algorithms
Which Neural Net Architectures Give Rise to Exploding and Vanishing Gradients?
A Bound on the Error of Cross Validation Using the Approximation and Estimation Rates, with Consequences for the Training-Test Split