yusuke1997/dblp-id-title huggingface dataset:
APDDv2: Aesthetics of Paintings and Drawings Dataset with Artist Labeled Scores and Comments
Stochastic Optimization of PCA with Capped MSG
Extremal Domain Translation with Neural Optimal Transport
Empowering Visible-Infrared Person Re-Identification with Large Foundation Models
Meta-learning families of plasticity rules in recurrent spiking networks using simulation-based inference
Expectation Propagation with Stochastic Kinetic Model in Complex Interaction Systems
SE(3)-Transformers: 3D Roto-Translation Equivariant Attention Networks
Products of Gaussians
Hierarchical Visual Feature Aggregation for OCR-Free Document Understanding
Training Energy-Based Normalizing Flow with Score-Matching Objectives
Federated Learning with Bilateral Curation for Partially Class-Disjoint Data
Activation Map Compression through Tensor Decomposition for Deep Learning
Efficient Moments-based Permutation Tests
Natural image synthesis for the retina with variational information bottleneck representation
Enhancing Chess Reinforcement Learning with Graph Representation
Scale Mixtures of Gaussians and the Statistics of Natural Images
A Bayesian Approach to Generative Adversarial Imitation Learning
Regularized Q-Learning
Understanding Dropout
Orthogonal Random Features
ArkVale: Efficient Generative LLM Inference with Recallable Key-Value Eviction
Efficient Learning of Continuous-Time Hidden Markov Models for Disease Progression
Uncertainty Quantification via Neural Posterior Principal Components
Cockpit: A Practical Debugging Tool for the Training of Deep Neural Networks
A Gang of Adversarial Bandits
Harnessing the power of choices in decision tree learning
See the Tree Through the Lines: The Shazoo Algorithm
SODA10M: A Large-Scale 2D Self/Semi-Supervised Object Detection Dataset for Autonomous Driving
Probabilistic Tensor Decomposition of Neural Population Spiking Activity
Finite-Sample Analysis for SARSA with Linear Function Approximation
The Implicit Bias of Adam on Separable Data
DiffInfinite: Large Mask-Image Synthesis via Parallel Random Patch Diffusion in Histopathology
What You See is What You Classify: Black Box Attributions
Learning Attractor Dynamics for Generative Memory
Approximate Bayesian Image Interpretation using Generative Probabilistic Graphics Programs
On Mixtures of Markov Chains
Complex Gated Recurrent Neural Networks
Learning Aspect Graph Representations from View Sequences
End-to-end Multi-modal Video Temporal Grounding
The Steering Approach for Multi-Criteria Reinforcement Learning
Firefly Neural Architecture Descent: a General Approach for Growing Neural Networks
OGB-LSC: A Large-Scale Challenge for Machine Learning on Graphs
Thwarting Adversarial Examples: An L_0-Robust Sparse Fourier Transform
Lookahead Bayesian Optimization with Inequality Constraints
PrivAuditor: Benchmarking Data Protection Vulnerabilities in LLM Adaptation Techniques
On Structured Prediction Theory with Calibrated Convex Surrogate Losses
Correctness of Belief Propagation in Gaussian Graphical Models of Arbitrary Topology
Proximity Operator of the Matrix Perspective Function and its Applications
Frequency Adaptive Normalization For Non-stationary Time Series Forecasting
Fair Sequential Selection Using Supervised Learning Models
ANAH-v2: Scaling Analytical Hallucination Annotation of Large Language Models
DropGNN: Random Dropouts Increase the Expressiveness of Graph Neural Networks
Symbol Grounding in Multimodal Sequences using Recurrent Neural Networks
FNP: Fourier Neural Processes for Arbitrary-Resolution Data Assimilation
A Discrete Variational Recurrent Topic Model without the Reparametrization Trick
Recovery of sparse linear classifiers from mixture of responses
L-TTA: Lightweight Test-Time Adaptation Using a Versatile Stem Layer
Discovering Potential Correlations via Hypercontractivity
Matching in Multi-arm Bandit with Collision
Gated Inference Network: Inference and Learning State-Space Models
Principal Neighbourhood Aggregation for Graph Nets
Agnostic Multi-Group Active Learning
Geometrical Singularities in the Neuromanifold of Multilayer Perceptrons
Neural Shuffle-Exchange Networks - Sequence Processing in O(n log n) Time
Triple descent and the two kinds of overfitting: where & why do they appear?
Consistent Multitask Learning with Nonlinear Output Relations
Diffusion Approximations for the Constant Step Size Backpropagation Algorithm and Resistance to Local Minima
Privacy Backdoors: Enhancing Membership Inference through Poisoning Pre-trained Models
Continuously Learning, Adapting, and Improving: A Dual-Process Approach to Autonomous Driving
Flattening Sharpness for Dynamic Gradient Projection Memory Benefits Continual Learning
Neural Machine Translation with Soft Prototype
Structure Learning in Human Sequential Decision-Making
Catastrophic Goodhart: regularizing RLHF with KL divergence does not mitigate heavy-tailed reward misspecification
Hyperkernels
FjORD: Fair and Accurate Federated Learning under heterogeneous targets with Ordered Dropout
Neural Foundations of Mental Simulation: Future Prediction of Latent Representations on Dynamic Scenes
Hokoff: Real Game Dataset from Honor of Kings and its Offline Reinforcement Learning Benchmarks
Bounded-Loss Private Prediction Markets
AdaFocal: Calibration-aware Adaptive Focal Loss
Learning Efficient Surrogate Dynamic Models with Graph Spline Networks
Semi-Open 3D Object Retrieval via Hierarchical Equilibrium on Hypergraph
The Potts-Ising model for discrete multivariate data
User-item fairness tradeoffs in recommendations
KLD-Sampling: Adaptive Particle Filters
Theoretical analysis of deep neural networks for temporally dependent observations
Differentially Private Distributed Data Summarization under Covariate Shift
Decision Mamba: A Multi-Grained State Space Model with Self-Evolution Regularization for Offline RL
CLIPDraw: Exploring Text-to-Drawing Synthesis through Language-Image Encoders
Stress-Testing Long-Context Language Models with Lifelong ICL and Task Haystack
Latent SDEs on Homogeneous Spaces
Graph Adversarial Self-Supervised Learning
Energetically Optimal Action Potentials
Average gradient outer product as a mechanism for deep neural collapse
Adversarial Style Augmentation for Domain Generalized Urban-Scene Segmentation
Constrained Adaptive Attack: Effective Adversarial Attack Against Deep Neural Networks for Tabular Data
Bridging the Domain Gap: Self-Supervised 3D Scene Understanding with Foundation Models
Self-Routing Capsule Networks
Provable General Function Class Representation Learning in Multitask Bandits and MDP
Facial Memory Is Kernel Density Estimation (Almost)
Probabilistic Missing Value Imputation for Mixed Categorical and Ordered Data
Outlier-Robust Distributionally Robust Optimization via Unbalanced Optimal Transport
MAUNet: Modality-Aware Anti-Ambiguity U-Net for Multi-Modality Cell Segmentation
WoodFisher: Efficient Second-Order Approximation for Neural Network Compression
Reconstructing perceived faces from brain activations with deep adversarial neural decoding
A hierarchical decomposition for explaining ML performance discrepancies
Accelerated Training of Physics-Informed Neural Networks (PINNs) using Meshless Discretizations
ViLCo-Bench: VIdeo Language COntinual learning Benchmark
GaussianCut: Interactive segmentation via graph cut for 3D Gaussian Splatting
Improved Bayes Risk Can Yield Reduced Social Welfare Under Competition
Tensorizing Neural Networks
ELLA: Exploration through Learned Language Abstraction
Altitude Training: Strong Bounds for Single-Layer Dropout
Untargeted Backdoor Watermark: Towards Harmless and Stealthy Dataset Copyright Protection
Res-Tuning: A Flexible and Efficient Tuning Paradigm via Unbinding Tuner from Backbone
Compressing Images by Encoding Their Latent Representations with Relative Entropy Coding
Semi-supervised Eigenvectors for Locally-biased Learning
BEIR: A Heterogeneous Benchmark for Zero-shot Evaluation of Information Retrieval Models
Specific and Shared Causal Relation Modeling and Mechanism-Based Clustering
Adaptively Growing Hierarchical Mixtures of Experts
ATMAN: Understanding Transformer Predictions Through Memory Efficient Attention Manipulation
Invertible Consistency Distillation for Text-Guided Image Editing in Around 7 Steps
Parallel Sampling of DP Mixture Models using Sub-Cluster Splits
Structured Dropout Variational Inference for Bayesian Neural Networks
SyMetric: Measuring the Quality of Learnt Hamiltonian Dynamics Inferred from Vision
EgoSim: An Egocentric Multi-view Simulator and Real Dataset for Body-worn Cameras during Motion and Activity
StrategyLLM: Large Language Models as Strategy Generators, Executors, Optimizers, and Evaluators for Problem Solving
Explainable and Efficient Randomized Voting Rules
Idempotent Learned Image Compression with Right-Inverse
Spectral Clustering with Perturbed Data
Optimal Cluster Recovery in the Labeled Stochastic Block Model
Distance Metric Learning with Application to Clustering with Side-Information
Not All Low-Pass Filters are Robust in Graph Convolutional Networks
High-Order Pooling for Graph Neural Networks with Tensor Decomposition
ResNet with one-neuron hidden layers is a Universal Approximator
Elliptical Perturbations for Differential Privacy
SQ Lower Bounds for Learning Mixtures of Linear Classifiers
Nonlinear Inverse Reinforcement Learning with Gaussian Processes
Weak Supervision Performance Evaluation via Partial Identification
Trading off Image Quality for Robustness is not Necessary with Regularized Deterministic Autoencoders
Exploring Large Feature Spaces with Hierarchical Multiple Kernel Learning
Risk-Averse Bayes-Adaptive Reinforcement Learning
Provably Transformers Harness Multi-Concept Word Semantics for Efficient In-Context Learning
A Probabilistic Framework for Deep Learning
ScaleCert: Scalable Certified Defense against Adversarial Patches with Sparse Superficial Layers
Deep Learning Games
Optical Diffusion Models for Image Generation
Winner-Take-All Column Row Sampling for Memory Efficient Adaptation of Language Model
Uncovering motifs of concurrent signaling across multiple neuronal populations
Sample Efficient Reinforcement Learning via Low-Rank Matrix Estimation
K-Radar: 4D Radar Object Detection for Autonomous Driving in Various Weather Conditions
Sparse Support Recovery with Non-smooth Loss Functions
SARDNET: A Self-Organizing Feature Map for Sequences
Optimal Comparator Adaptive Online Learning with Switching Cost
Rethinking Semi-Supervised Imbalanced Node Classification from Bias-Variance Decomposition
Not too little, not too much: a theoretical analysis of graph (over)smoothing
Towards Open Respiratory Acoustic Foundation Models: Pretraining and Benchmarking
Estimating time-varying input signals and ion channel states from a single voltage trace of a neuron
An Efficient Recipe for Long Context Extension via Middle-Focused Positional Encoding
Diffusion PID: Interpreting Diffusion via Partial Information Decomposition
Fast Learning with Predictive Forward Models
A Fourier Perspective on Model Robustness in Computer Vision
Gaussian Process Latent Variable Models for Visualisation of High Dimensional Data
Few-shot Learning for Feature Selection with Hilbert-Schmidt Independence Criterion
CARD: Classification and Regression Diffusion Models
Dual Encoder GAN Inversion for High-Fidelity 3D Head Reconstruction from Single Images
Optimal Block-wise Asymmetric Graph Construction for Graph-based Semi-supervised Learning
User-Specified Local Differential Privacy in Unconstrained Adaptive Online Learning
Learning to Decompose and Disentangle Representations for Video Prediction
Characterizing Neural Gain Control using Spike-triggered Covariance
SAViT: Structure-Aware Vision Transformer Pruning via Collaborative Optimization
On the Parameterization and Initialization of Diagonal State Space Models
Successor Features for Transfer in Reinforcement Learning
SpArSe: Sparse Architecture Search for CNNs on Resource-Constrained Microcontrollers
BML: A High-performance, Low-cost Gradient Synchronization Algorithm for DML Training
Learning Switching Linear Models of Human Motion
CEBaB: Estimating the Causal Effects of Real-World Concepts on NLP Model Behavior
Dynamic Social Network Analysis using Latent Space Models
A Credit Assignment Compiler for Joint Prediction
Rethinking Optimal Transport in Offline Reinforcement Learning
Constructing Unrestricted Adversarial Examples with Generative Models
Submodular Meta-Learning
Solving Marginal MAP Problems with NP Oracles and Parity Constraints
Near-Optimal Regret for Adversarial MDP with Delayed Bandit Feedback
Exploring evolution-aware & -free protein language models as protein function predictors
A Universal Catalyst for First-Order Optimization
Stochastic Chebyshev Gradient Descent for Spectral Optimization
Causal Discovery in Heterogeneous Environments Under the Sparse Mechanism Shift Hypothesis
Is Deeper Better only when Shallow is Good?
Implicit Transformer Network for Screen Content Image Continuous Super-Resolution
Estimation of Information Theoretic Measures for Continuous Random Variables
An Analog VLSI Model of Periodicity Extraction
M3Exam: A Multilingual, Multimodal, Multilevel Benchmark for Examining Large Language Models
Improved Techniques for Training GANs
Noise Suppression Based on Neurophysiologically-motivated SNR Estimation for Robust Speech Recognition
One Less Reason for Filter Pruning: Gaining Free Adversarial Robustness with Structured Grouped Kernel Pruning
Tomography of the London Underground: a Scalable Model for Origin-Destination Data
Generalized Learning Vector Quantization
Deep Graph Neural Networks via Posteriori-Sampling-based Node-Adaptative Residual Module
Cappy: Outperforming and Boosting Large Multi-Task LMs with a Small Scorer
Hyperparameter Tuning is All You Need for LISTA
Bridge the Gap Between Architecture Spaces via A Cross-Domain Predictor
Partial Matrix Completion
Proximal SCOPE for Distributed Sparse Learning
VastTrack: Vast Category Visual Object Tracking
Imbalance Trouble: Revisiting Neural-Collapse Geometry
A Self-organizing Associative Memory System for Control Applications
Analogy Making and Logical Inferences on Images using Cellular Automata based Hyperdimensional Computing
Discovering Structure in High-Dimensional Data Through Correlation Explanation
Fair Algorithms for Multi-Agent Multi-Armed Bandits
A systematic approach to extracting semantic information from functional MRI data
Functional form of motion priors in human motion perception
To Believe or Not to Believe Your LLM: Iterative Prompting for Estimating Epistemic Uncertainty
Read and Reap the Rewards: Learning to Play Atari with the Help of Instruction Manuals
Direct Advantage Estimation
Bisimulation Metrics are Optimal Transport Distances, and Can be Computed Efficiently
A Learning Error Analysis for Structured Prediction with Approximate Inference
Object landmark discovery through unsupervised adaptation
Minimax Optimal Estimation of Approximate Differential Privacy on Neighboring Databases
Approximating mutual information of high-dimensional variables using learned representations
Wavelets on Graphs via Deep Learning
Online EXP3 Learning in Adversarial Bandits with Delayed Feedback
Towards Sample-efficient Overparameterized Meta-learning
On Warm-Starting Neural Network Training
Few-shot Relational Reasoning via Connection Subgraph Pretraining
Online Continual Learning with Maximal Interfered Retrieval
Temporal Difference Learning in Continuous Time and Space
Adversarial Robustness in Graph Neural Networks: A Hamiltonian Approach
Fast Axiomatic Attribution for Neural Networks
Semi-supervised Protein Classification Using Cluster Kernels
Diffusion Models as Plug-and-Play Priors
DEBAGREEMENT: A comment-reply dataset for (dis)agreement detection in online debates
Parameter Expanded Variational Bayesian Methods
Incorporating Interpretable Output Constraints in Bayesian Neural Networks
Splitting Steepest Descent for Growing Neural Architectures
Visual Cortex Circuitry and Orientation Tuning
Extracting Tree-Structured Representations of Trained Networks
Task-oriented Time Series Imputation Evaluation via Generalized Representers
Spectral Invariant Learning for Dynamic Graphs under Distribution Shifts
EEGPT: Pretrained Transformer for Universal and Reliable Representation of EEG Signals
RAW: A Robust and Agile Plug-and-Play Watermark Framework for AI-Generated Images with Provable Guarantees
Neural Flows: Efficient Alternative to Neural ODEs
A Rational Analysis of Cognitive Control in a Speeded Discrimination Task
A Generative Model of Symmetry Transformations
A Regression Approach to Learning-Augmented Online Algorithms
Gaussian Process Conditional Density Estimation
A PAC-Bayesian Generalization Bound for Equivariant Networks
Rapid Distance-Based Outlier Detection via Sampling
Gaussian Processes for Regression
Distribution-free binary classification: prediction sets, confidence intervals and calibration
Dynamic Neural Regeneration: Enhancing Deep Learning Generalization on Small Datasets
The Computation of Stereo Disparity for Transparent and for Opaque Surfaces
Reduction Algorithms for Persistence Diagrams of Networks: CoralTDA and PrunIT
On the Pareto Front of Multilingual Neural Machine Translation
PoET: A generative model of protein families as sequences-of-sequences
Online Multi-Armed Bandits with Adaptive Inference
CTIBench: A Benchmark for Evaluating LLMs in Cyber Threat Intelligence
Coevolutionary Latent Feature Processes for Continuous-Time User-Item Interactions
Rate-Optimal Subspace Estimation on Random Graphs
Towards Editing Time Series
Bayesian Estimation of Latently-grouped Parameters in Undirected Graphical Models
LLM-Check: Investigating Detection of Hallucinations in Large Language Models
Is Your Code Generated by ChatGPT Really Correct? Rigorous Evaluation of Large Language Models for Code Generation
Neural Dynamic Policies for End-to-End Sensorimotor Learning
Bayesian Control of Large MDPs with Unknown Dynamics in Data-Poor Environments
Graph Cross Networks with Vertex Infomax Pooling
On Learning Ising Models under Huber's Contamination Model
Signal Processing for Implicit Neural Representations
AdaBoost is Consistent
Multi-body SE(3) Equivariance for Unsupervised Rigid Segmentation and Motion Estimation
Coresets for Near-Convex Functions
Time-FFM: Towards LM-Empowered Federated Foundation Model for Time Series Forecasting
You Only Condense Once: Two Rules for Pruning Condensed Datasets
MoVQ: Modulating Quantized Vectors for High-Fidelity Image Generation
Representation Learning on Spatial Networks
Coupling Nonparametric Mixtures via Latent Dirichlet Processes
Experiences with Bayesian Learning in a Real World Application
Chefs' Random Tables: Non-Trigonometric Random Features
A Spoken Language Dataset of Descriptions for Speech-Based Grounded Language Learning
Accelerating Motion Planning via Optimal Transport
Distribution-Free Statistical Dispersion Control for Societal Applications
Recursive ICA
The Generalized Reparameterization Gradient
A Computationally Efficient Method for Learning Exponential Family Distributions
OpenDlign: Open-World Point Cloud Understanding with Depth-Aligned Images
Reward Mapping for Transfer in Long-Lived Agents
Targeted Sequential Indirect Experiment Design
Distributionally Robust Logistic Regression
MeGraph: Capturing Long-Range Interactions by Alternating Local and Hierarchical Aggregation on Multi-Scaled Graph Hierarchy
Optimal Algorithms for Decentralized Stochastic Variational Inequalities
Using the Equivalent Kernel to Understand Gaussian Process Regression
Interval timing in deep reinforcement learning agents
Generalized and Discriminative Few-Shot Object Detection via SVD-Dictionary Enhancement
Learning Augmented Energy Minimization via Speed Scaling
BitsFusion: 1.99 bits Weight Quantization of Diffusion Model
Coulomb Classifiers: Generalizing Support Vector Machines via an Analogy to Electrostatic Systems
Online Agnostic Multiclass Boosting
Agnostic Learning with Multiple Objectives
Learning-Augmented Approximation Algorithms for Maximum Cut and Related Problems
Volume Rendering of Neural Implicit Surfaces
Two-Stream Network for Sign Language Recognition and Translation
DU-Shapley: A Shapley Value Proxy for Efficient Dataset Valuation
Self-Predictive Universal AI
How to Start Training: The Effect of Initialization and Architecture
Probabilistic Weight Fixing: Large-scale training of neural network weight uncertainties for quantisation
Neural Dynamics of Motion Segmentation and Grouping
On Learning Markov Chains
MARBLE: Music Audio Representation Benchmark for Universal Evaluation
Uncertainty-aware Self-training for Few-shot Text Classification
Invariant Object Recognition Using a Distributed Associative Memory
Unified Graph Augmentations for Generalized Contrastive Learning on Graphs
Learning Latent Subspaces in Variational Autoencoders
Learning Generative Models with Visual Attention
DENETHOR: The DynamicEarthNET dataset for Harmonized, inter-Operable, analysis-Ready, daily crop monitoring from space
Unsupervised learning of object structure and dynamics from videos
Structure from Duplicates: Neural Inverse Graphics from a Pile of Objects
PIE-NET: Parametric Inference of Point Cloud Edges
Understanding Transformer Reasoning Capabilities via Graph Algorithms
Learning Student-Friendly Teacher Networks for Knowledge Distillation
Operators and Curried Functions: Training and Analysis of Simple Recurrent Networks
Robust Generalized Method of Moments: A Finite Sample Viewpoint
Optimal Rates for Random Fourier Features
Escaping from the Barren Plateau via Gaussian Initializations in Deep Variational Quantum Circuits
Acceleration in Distributed Sparse Regression
Tri-Level Navigator: LLM-Empowered Tri-Level Learning for Time Series OOD Generalization
Expressive power of tensor-network factorizations for probabilistic modeling
Variance Reduction for Matrix Games
Generating Datasets of 3D Garments with Sewing Patterns
SMILe: Scalable Meta Inverse Reinforcement Learning through Context-Conditional Policies
A Unified Framework for U-Net Design and Analysis
Temporal alignment and latent Gaussian process factor inference in population spike trains
Techniques for Symbol Grounding with SATNet
Minimax Probability Machine
Contextual Linear Optimization with Bandit Feedback
Adaptive Test-Time Personalization for Federated Learning
Learning Frequency Domain Approximation for Binary Neural Networks
Concentration of Multilinear Functions of the Ising Model with Applications to Network Data
Exact MAP Estimates by (Hyper)tree Agreement
Transition Point Dynamic Programming
ProteinNPT: Improving protein property prediction and design with non-parametric transformers
Sense and Sensitivity Analysis: Simple Post-Hoc Analysis of Bias Due to Unobserved Confounding
Diversity vs. Recognizability: Human-like generalization in one-shot generative models
GraphFormers: GNN-nested Transformers for Representation Learning on Textual Graph
Mitigating Forgetting in Online Continual Learning with Neuron Calibration
Improving the Learning Capability of Small-size Image Restoration Network by Deep Fourier Shifting
Maximizing and Satisficing in Multi-armed Bandits with Graph Information
Distributionally Robust Performative Prediction
Robust Optimal Transport with Applications in Generative Modeling and Domain Adaptation
K-Nearest-Neighbor Local Sampling Based Conditional Independence Testing
Fitting trees to 𝓁 1 -hyperbolic distances
What Can the Neural Tangent Kernel Tell Us About Adversarial Robustness?
Why MCA? Nonlinear sparse coding with spike-and-slab prior for neurally plausible image encoding
Finite Population Regression Adjustment and Non-asymptotic Guarantees for Treatment Effect Estimation
Believe What You See: Implicit Constraint Approach for Offline Multi-Agent Reinforcement Learning
Consistency Regularization for Variational Auto-Encoders
A Computational Model for Cursive Handwriting Based on the Minimization Principle
COBE: Contextualized Object Embeddings from Narrated Instructional Video
Optimizing Data Collection for Machine Learning
Neural Jump Stochastic Differential Equations
Learning from Aggregate Observations
Dataset Diffusion: Diffusion-based Synthetic Data Generation for Pixel-Level Semantic Segmentation
Natural Actor-Critic for Road Traffic Optimisation