yusuke1997/dblp-id-title huggingface dataset:
A Batch-to-Online Transformation under Random-Order Model
Continuously Tempered PDMP samplers
DynaBERT: Dynamic BERT with Adaptive Width and Depth
TripletCLIP: Improving Compositional Reasoning of CLIP via Synthetic Vision-Language Negatives
Unfolding the Alternating Optimization for Blind Super Resolution
The Target-Charging Technique for Privacy Analysis across Interactive Computations
Efficient Reinforcement Learning for High Dimensional Linear Quadratic Systems
Lip to Speech Synthesis with Visual Context Attentional GAN
When Expressivity Meets Trainability: Fewer than $n$ Neurons Can Work
TREC: Transient Redundancy Elimination-based Convolution
Fixed Point Analysis for Recurrent Networks
Compositionality, MDL Priors, and Object Recognition
A General Framework for Robust Interactive Learning
Bayesian nonparametric models for ranked data
Align before Fuse: Vision and Language Representation Learning with Momentum Distillation
Focus on Query: Adversarial Mining Transformer for Few-Shot Segmentation
Self-Distillation as Instance-Specific Label Smoothing
Morphogenesis of the Lateral Geniculate Nucleus: How Singularities Affect Global Structure
On the Distribution of the Number of Local Minima of a Random Function on a Graph
Where Did I Come From? Origin Attribution of AI-Generated Images
Sparse Estimation with Structured Dictionaries
Cheaply Estimating Inference Efficiency Metrics for Autoregressive Transformer Models
A Gang of Bandits
A Structure-Aware Framework for Learning Device Placements on Computation Graphs
Blind Attacks on Machine Learners
The Power of Asymmetry in Binary Hashing
Semi-Supervised Sparse Gaussian Classification: Provable Benefits of Unlabeled Data
RMM: Reinforced Memory Management for Class-Incremental Learning
ColJailBreak: Collaborative Generation and Editing for Jailbreaking Text-to-Image Deep Generation
Deep Learning without Weight Transport
Prompt Tuning Strikes Back: Customizing Foundation Models with Low-Rank Prompt Adaptation
BRP-NAS: Prediction-based NAS using GCNs
Efficient Test-Time Adaptation for Super-Resolution with Second-Order Degradation and Reconstruction
Neural Program Meta-Induction
AutoWS-Bench-101: Benchmarking Automated Weak Supervision with 100 Labels
Grammatical Bigrams
Drop, Swap, and Generate: A Self-Supervised Approach for Generating Neural Activity
Stochastic variational inference for hidden Markov models
Efficient Computation of Complex Distance Metrics Using Hierarchical Filtering
Exogenous Matching: Learning Good Proposals for Tractable Counterfactual Estimation
Monoculture in Matching Markets
Practical Issues in Temporal Difference Learning
Online Decision Based Visual Tracking via Reinforcement Learning
Extracting Deformation-Aware Local Features by Learning to Deform
The Price of Implicit Bias in Adversarially Robust Generalization
XAGen: 3D Expressive Human Avatars Generation
Optimal Sample Complexity of M-wise Data for Top-K Ranking
On the Learning Mechanisms in Physical Reasoning
Learning from Active Human Involvement through Proxy Value Propagation
Collaborative Decision Making Using Action Suggestions
Federated Conditional Stochastic Optimization
Robust Transfer Principal Component Analysis with Rank Constraints
Variance Reduction in Monte-Carlo Tree Search
NeuroClips: Towards High-fidelity and Smooth fMRI-to-Video Reconstruction
Generalised Bayesian Filtering via Sequential Monte Carlo
PAC Reinforcement Learning with Rich Observations
An online Hebbian learning rule that performs Independent Component Analysis
Use of Bad Training Data for Better Predictions
Data Free Backdoor Attacks
Kalman Normalization: Normalizing Internal Representations Across Network Layers
Deep State Space Models for Time Series Forecasting
NurViD: A Large Expert-Level Video Database for Nursing Procedure Activity Understanding
Sparse probabilistic projections
Joint Feature and Differentiable k-NN Graph Learning using Dirichlet Energy
Sample Complexity of Automated Mechanism Design
A Model of Recurrent Interactions in Primary Visual Cortex
Private Non-smooth ERM and SCO in Subquadratic Steps
Encoding Time-Series Explanations through Self-Supervised Model Behavior Consistency
Trade-off between Payoff and Model Rewards in Shapley-Fair Collaborative Machine Learning
NVFi: Neural Velocity Fields for 3D Physics Learning from Dynamic Videos
Poincaré Recurrence, Cycles and Spurious Equilibria in Gradient-Descent-Ascent for Non-Convex Non-Concave Zero-Sum Games
Unsupervised Noise Adaptive Speech Enhancement by Discriminator-Constrained Optimal Transport
Dual-Personalizing Adapter for Federated Foundation Models
An Architecture for Deep, Hierarchical Generative Models
Fairness Reprogramming
An Asymptotically Optimal Primal-Dual Incremental Algorithm for Contextual Linear Bandits
SEVIR : A Storm Event Imagery Dataset for Deep Learning Applications in Radar and Satellite Meteorology
Policy Search by Dynamic Programming
A New Neural Kernel Regime: The Inductive Bias of Multi-Task Learning
Cross-lingual Retrieval for Iterative Self-Supervised Training
Distribution Learning with Valid Outputs Beyond the Worst-Case
H3T: Efficient Integration of Memory Optimization and Parallelism for Large-scale Transformer Training
Chatting Makes Perfect: Chat-based Image Retrieval
Local Aggregative Games
Antigen-Specific Antibody Design and Optimization with Diffusion-Based Generative Models for Protein Structures
Causal Shapley Values: Exploiting Causal Knowledge to Explain Individual Predictions of Complex Models
Same-Cluster Querying for Overlapping Clusters
Understanding the Expressive Power and Mechanisms of Transformer for Sequence Modeling
Temporal Robustness against Data poisoning
Concept Distillation: Leveraging Human-Centered Explanations for Model Improvement
It Has Potential: Gradient-Driven Denoisers for Convergent Solutions to Inverse Problems
Superset Technique for Approximate Recovery in One-Bit Compressed Sensing
A Computational Model of Eye Movements during Object Class Detection
Fine-Grained Cross-View Geo-Localization Using a Correlation-Aware Homography Estimator
Setting the Trap: Capturing and Defeating Backdoors in Pretrained Language Models through Honeypots
Almost Horizon-Free Structure-Aware Best Policy Identification with a Generative Model
Improved Hidden Markov Models Speech Recognition Using Radial Basis Function Networks
Hessian-based Analysis of Large Batch Training and Robustness to Adversaries
Learning in Generalized Linear Contextual Bandits with Stochastic Delays
Uniform convergence may be unable to explain generalization in deep learning
Prediction strategies without loss
Reconstruction on Trees and Low-Degree Polynomials
Resolving the data ambiguity for periodic crystals
Constant-Time Loading of Shallow 1-Dimensional Networks
Partial success in closing the gap between human and machine vision
Learning Equilibria in Matching Markets from Bandit Feedback
Learning with a Wasserstein Loss
Accurate Point Cloud Registration with Robust Optimal Transport
Understanding Visual Feature Reliance through the Lens of Complexity
Improved Precision and Recall Metric for Assessing Generative Models
Identifying Structure across Pre-partitioned Data
ViewFool: Evaluating the Robustness of Visual Recognition to Adversarial Viewpoints
FouRA: Fourier Low-Rank Adaptation
PPi: Pretraining Brain Signal Model for Patient-independent Seizure Detection
On the Role of Attention Masks and LayerNorm in Transformers
Concurrent Object Recognition and Segmentation by Graph Partitioning
Fair Infinitesimal Jackknife: Mitigating the Influence of Biased Training Data Points Without Refitting
Variational Inference for Mahalanobis Distance Metrics in Gaussian Process Regression
Ess-InfoGAIL: Semi-supervised Imitation Learning from Imbalanced Demonstrations
Differentially Private k-Means with Constant Multiplicative Error
Mind the Gap: Understanding the Modality Gap in Multi-modal Contrastive Representation Learning
Decision trees as partitioning machines to characterize their generalization properties
Image Inpainting via Generative Multi-column Convolutional Neural Networks
Closed-Form Inversion of Backpropagation Networks
GAUCHE: A Library for Gaussian Processes in Chemistry
Gradient-Variation Online Learning under Generalized Smoothness
Unveiling and Mitigating Backdoor Vulnerabilities based on Unlearning Weight Changes and Backdoor Activeness
Shrinking the Tube: A New Support Vector Regression Algorithm
Spike Frequency Adaptation Implements Anticipative Tracking in Continuous Attractor Neural Networks
Score-based Generative Models with Lévy Processes
Machine Learning for Variance Reduction in Online Experiments
Bayesian dark knowledge
Learning Multiple Tasks with a Sparse Matrix-Normal Penalty
Wild-Time: A Benchmark of in-the-Wild Distribution Shift over Time
R-FCN: Object Detection via Region-based Fully Convolutional Networks
Smoothed analysis of the low-rank approach for smooth semidefinite programs
On the Provable Generalization of Recurrent Neural Networks
Diverse Sequential Subset Selection for Supervised Video Summarization
Evidential Softmax for Sparse Multimodal Distributions in Deep Generative Models
Simualtion of a Thalamocortical Circuit for Computing Directional Heading in the Rat
No Representation Rules Them All in Category Discovery
Precipitation Downscaling with Spatiotemporal Video Diffusion
Towards Understanding the Mixture-of-Experts Layer in Deep Learning
Synchrony Detection by Analogue VLSI Neurons with Bimodal STDP Synapses
DOSE: Diffusion Dropout with Adaptive Prior for Speech Enhancement
Optimal Shrinkage of Singular Values Under Random Data Contamination
SoftPatch: Unsupervised Anomaly Detection with Noisy Data
Path Regularization: A Convexity and Sparsity Inducing Regularization for Parallel ReLU Networks
AI for Interpretable Chemistry: Predicting Radical Mechanistic Pathways via Contrastive Learning
VaRT: Variational Regression Trees
Explainable Reinforcement Learning via Model Transforms
Surround Modulation: A Bio-inspired Connectivity Structure for Convolutional Neural Networks
Structural Pruning via Latency-Saliency Knapsack
Physics-Informed Regularization for Domain-Agnostic Dynamical System Modeling
Rethinking the Diffusion Models for Missing Data Imputation: A Gradient Flow Perspective
An Unsupervised Information-Theoretic Perceptual Quality Metric
Dissecting the Diffusion Process in Linear Graph Convolutional Networks
The Implicit Bias of Gradient Descent on Separable Multiclass Data
Operator World Models for Reinforcement Learning
On the Role of Information Structure in Reinforcement Learning for Partially-Observable Sequential Teams and Games
Faster Differentially Private Top-k Selection: A Joint Exponential Mechanism with Pruning
L 2 -Uniform Stability of Randomized Learning Algorithms: Sharper Generalization Bounds and Confidence Boosting
Layered Dynamic Textures
Post Hoc Explanations of Language Models Can Improve Language Models
Program Synthesis with Pragmatic Communication
Structured Learning via Logistic Regression
Telescoping Density-Ratio Estimation
Online Stochastic Shortest Path with Bandit Feedback and Unknown Transition Function
Multivariate Time-Series Forecasting with Temporal Polynomial Graph Neural Networks
Regularized Molecular Conformation Fields
Clone MCMC: Parallel High-Dimensional Gaussian Gibbs Sampling
Sparse Feature Learning for Deep Belief Networks
Competition Among Networks Improves Committee Performance
Learning to localise sounds with spiking neural networks
Scalable Hyperparameter Transfer Learning
Subspace Attack: Exploiting Promising Subspaces for Query-Efficient Black-box Attacks
IPMix: Label-Preserving Data Augmentation Method for Training Robust Classifiers
CorresNeRF: Image Correspondence Priors for Neural Radiance Fields
An Information Theoretic Approach to the Functional Classification of Neurons
Distributional Successor Features Enable Zero-Shot Policy Optimization
DoReMi: Optimizing Data Mixtures Speeds Up Language Model Pretraining
On the Similarity between the Laplace and Neural Tangent Kernels
Online Decision Mediation
Neural Temporal-Difference Learning Converges to Global Optima
Unsupervised Detection of Regions of Interest Using Iterative Link Analysis
Probabilistic Active Meta-Learning
From Instance Training to Instruction Learning: Task Adapters Generation from Instructions
Conformalized Time Series with Semantic Features
An Efficient Asynchronous Method for Integrating Evolutionary and Gradient-based Policy Search
Robust Recursive Partitioning for Heterogeneous Treatment Effects with Uncertainty Quantification
dattri: A Library for Efficient Data Attribution
Scaling Laws with Vocabulary: Larger Models Deserve Larger Vocabularies
Learning with Consistency between Inductive Functions and Kernels
$C^2M^3$: Cycle-Consistent Multi-Model Merging
The Simplicity Bias in Multi-Task RNNs: Shared Attractors, Reuse of Dynamics, and Geometric Representation
Estimating the Size of a Large Network and its Communities from a Random Sample
Regret Bounds for Gaussian-Process Optimization in Large Domains
Intra-Modal Proxy Learning for Zero-Shot Visual Categorization with CLIP
Is Function Similarity Over-Engineered? Building a Benchmark
ACFun: Abstract-Concrete Fusion Facial Stylization
G2SAT: Learning to Generate SAT Formulas
Block Low-Rank Preconditioner with Shared Basis for Stochastic Optimization
A convex program for bilinear inversion of sparse vectors
Dynamics of Analog Neural Networks with Time Delay
Benchmarking Multi-Agent Deep Reinforcement Learning Algorithms in Cooperative Tasks
Min-Max Propagation
Rethinking LDA: Why Priors Matter
Causal Effect Identification in Uncertain Causal Networks
PURE: Prompt Evolution with Graph ODE for Out-of-distribution Fluid Dynamics Modeling
List-Decodable Mean Estimation in Nearly-PCA Time
Probabilistic inverse optimal control for non-linear partially observable systems disentangles perceptual uncertainty and behavioral costs
Dynamic Mode Decomposition with Reproducing Kernels for Koopman Spectral Analysis
Evaluating Gradient Inversion Attacks and Defenses in Federated Learning
Trash or Treasure? An Interactive Dual-Stream Strategy for Single Image Reflection Separation
Graph-based Consensus Maximization among Multiple Supervised and Unsupervised Models
A New Theory for Matrix Completion
StoryBench: A Multifaceted Benchmark for Continuous Story Visualization
Trust Issues: Uncertainty Estimation Does Not Enable Reliable OOD Detection On Medical Tabular Data
Batch Normalization Orthogonalizes Representations in Deep Random Networks
Physics-Informed Implicit Representations of Equilibrium Network Flows
NoiseGPT: Label Noise Detection and Rectification through Probability Curvature
pFL-Bench: A Comprehensive Benchmark for Personalized Federated Learning
An Iterative Improvement Procedure for Hierarchical Clustering
V-PETL Bench: A Unified Visual Parameter-Efficient Transfer Learning Benchmark
Large-batch Optimization for Dense Visual Predictions: Training Faster R-CNN in 4.2 Minutes
MACE: Higher Order Equivariant Message Passing Neural Networks for Fast and Accurate Force Fields
Deep Homogeneous Mixture Models: Representation, Separation, and Approximation
Matrix Completion has No Spurious Local Minimum
Optimistic Exploration in Reinforcement Learning Using Symbolic Model Estimates
LaKD: Length-agnostic Knowledge Distillation for Trajectory Prediction with Any Length Observations
ElasTST: Towards Robust Varied-Horizon Forecasting with Elastic Time-Series Transformer
Online Adaptive Methods, Universality and Acceleration
Learning One Representation to Optimize All Rewards
Loop Series and Bethe Variational Bounds in Attractive Graphical Models
Fragment-based Pretraining and Finetuning on Molecular Graphs
Hidden Markov Models in Molecular Biology: New Algorithms and Applications
Reward Machines for Deep RL in Noisy and Uncertain Environments
Positive-Unlabeled Compression on the Cloud
EvoFed: Leveraging Evolutionary Strategies for Communication-Efficient Federated Learning
Synthesizing Robust Plans under Incomplete Domain Models
Towards Social Robots: Automatic Evaluation of Human-robot Interaction by Face Detection and Expression Classification
CROCS: Clustering and Retrieval of Cardiac Signals Based on Patient Disease Class, Sex, and Age
Capturing the denoising effect of PCA via compression ratio
Polynomial-Time Computation of Optimal Correlated Equilibria in Two-Player Extensive-Form Games with Public Chance Moves and Beyond
Nonlocal Attention Operator: Materializing Hidden Knowledge Towards Interpretable Physics Discovery
Better Algorithms for Individually Fair k -Clustering
Parameter-free Dynamic Graph Embedding for Link Prediction
Bayesian Ensemble Learning
Improving multimodal datasets with image captioning
GeoDE: a Geographically Diverse Evaluation Dataset for Object Recognition
Benchmarking Multimodal AutoML for Tabular Data with Text Fields
Predicting Training Time Without Training
Optimizing Generalized PageRank Methods for Seed-Expansion Community Detection
Affine Independent Variational Inference
Robust Data Valuation with Weighted Banzhaf Values
Learning MDPs from Features: Predict-Then-Optimize for Sequential Decision Making by Reinforcement Learning
Initialization of ReLUs for Dynamical Isometry
Learning a Metric Embedding for Face Recognition using the Multibatch Method
Learning Knowledge Graph-based World Models of Textual Environments
Eliciting Thinking Hierarchy without a Prior
Learning a High Fidelity Pose Invariant Model for High-resolution Face Frontalization
Forward-Decoding Kernel-Based Phone Recognition
DFNets: Spectral CNNs for Graphs with Feedback-Looped Filters
Beyond Exchangeability: The Chinese Voting Process
AmadeusGPT: a natural language interface for interactive animal behavioral analysis
Mean Field for the Stochastic Blockmodel: Optimization Landscape and Convergence Issues
EpiCare: A Reinforcement Learning Benchmark for Dynamic Treatment Regimes
Can Language Models Learn to Skip Steps?
Fixing Max-Product: Convergent Message Passing Algorithms for MAP LP-Relaxations
Using noise to probe recurrent neural network structure and prune synapses
Online Learning in Periodic Zero-Sum Games
SurgicAI: A Hierarchical Platform for Fine-Grained Surgical Policy Learning and Benchmarking
Image Retrieval and Classification Using Local Distance Functions
Mnemosyne: Learning to Train Transformers with Transformers
Reliable Causal Discovery with Improved Exact Search and Weaker Assumptions
Asymptotic Properties for Bayesian Neural Network in Besov Space
Parkinsonian {C
CATs: Cost Aggregation Transformers for Visual Correspondence
Rethinking Space-Time Networks with Improved Memory Coverage for Efficient Video Object Segmentation
Geometric Analysis of Nonlinear Manifold Clustering
Patch2Self: Denoising Diffusion MRI with Self-Supervised Learning​
Efficient Gradient Computation for Structured Output Learning with Rational and Tropical Losses
Best-case lower bounds in online learning
StreamBench: Towards Benchmarking Continuous Improvement of Language Agents
Towards Hardware-Aware Tractable Learning of Probabilistic Models
SubseasonalClimateUSA: A Dataset for Subseasonal Forecasting and Benchmarking
The Smoothed Possibility of Social Choice
Learned Prioritization for Trading Off Accuracy and Speed
Likelihood Ratios for Out-of-Distribution Detection
Provably Efficient Reward-Agnostic Navigation with Linear Value Iteration
Learning Hybrid Models for Image Annotation with Partially Labeled Data
Coding efficiency and detectability of rate fluctuations with non-Poisson neuronal firing
MambaTalk: Efficient Holistic Gesture Synthesis with Selective State Space Models
CoVoMix: Advancing Zero-Shot Speech Generation for Human-like Multi-talker Conversations
Subwords as Skills: Tokenization for Sparse-Reward Reinforcement Learning
True Few-Shot Learning with Language Models
BLURD: Benchmarking and Learning using a Unified Rendering and Diffusion Model
Wavelet regression and additive models for irregularly spaced data
The Origins and Prevalence of Texture Bias in Convolutional Neural Networks
Detection as Regression: Certified Object Detection with Median Smoothing
Navigating the Safety Landscape: Measuring Risks in Finetuning Large Language Models
Neural Additive Models: Interpretable Machine Learning with Neural Nets
From Distribution Learning in Training to Gradient Search in Testing for Combinatorial Optimization
Large Language Models are Fixated by Red Herrings: Exploring Creative Problem Solving and Einstellung Effect using the Only Connect Wall Dataset
Learning Descriptive Image Captioning via Semipermeable Maximum Likelihood Estimation
Natural Language Grounded Multitask Navigation
Distilling Meta Knowledge on Heterogeneous Graph for Illicit Drug Trafficker Detection on Social Media
Exploiting Representation Curvature for Boundary Detection in Time Series
Fair GLASSO: Estimating Fair Graphical Models with Unbiased Statistical Behavior
Convolutional LSTM Network: A Machine Learning Approach for Precipitation Nowcasting
Noether's Learning Dynamics: Role of Symmetry Breaking in Neural Networks
Reversible Recurrent Neural Networks
Ensemble-based Deep Reinforcement Learning for Vehicle Routing Problems under Distribution Shift
Vision-Language Navigation with Energy-Based Policy
Optimizing Solution-Samplers for Combinatorial Problems: The Landscape of Policy-Gradient Method
On the Adversarial Robustness of Mixture of Experts
Kernel PCA for Out-of-Distribution Detection
Private Set Generation with Discriminative Information
BayesPCN: A Continually Learnable Predictive Coding Associative Memory
A Latent Source Model for Nonparametric Time Series Classification
Efficient Contextual Bandits with Continuous Actions
Global Regularization of Inverse Kinematics for Redundant Manipulators
Modelling heterogeneous distributions with an Uncountable Mixture of Asymmetric Laplacians
A Global Health Gym Environment for RL Applications
Grounded Decoding: Guiding Text Generation with Grounded Models for Embodied Agents
CatBoost: unbiased boosting with categorical features
On the number of variables to use in principal component regression
Adversarial Bandits with Corruptions: Regret Lower Bound and No-regret Algorithm
A Closer Look at Prototype Classifier for Few-shot Image Classification
A Robust and Opponent-Aware League Training Method for StarCraft II
Structural epitome: a way to summarize one's visual experience
Not All Neuro-Symbolic Concepts Are Created Equal: Analysis and Mitigation of Reasoning Shortcuts
Federated Multi-Objective Learning
Stochastic Structured Prediction under Bandit Feedback
Accelerating Training of Transformer-Based Language Models with Progressive Layer Dropping
Locally differentially private estimation of functionals of discrete distributions
Pandora's Box: Towards Building Universal Attackers against Real-World Large Vision-Language Models
Neural Topographic Factor Analysis for fMRI Data
Interpreting Neural Response Variability as Monte Carlo Sampling of the Posterior
NeuroMLR: Robust & Reliable Route Recommendation on Road Networks
STEVE-1: A Generative Model for Text-to-Behavior in Minecraft
Dual Policy Iteration
Perceptual Attacks of No-Reference Image Quality Models with Human-in-the-Loop
Optimal Stochastic and Online Learning with Individual Iterates
Risk Sensitive Reinforcement Learning
Mitigating Backdoor Attack by Injecting Proactive Defensive Backdoor
Causal Intervention for Weakly-Supervised Semantic Segmentation
Submanifold density estimation
FAST: a Fused and Accurate Shrinkage Tree for Heterogeneous Treatment Effects Estimation
Spectral Evolution and Invariance in Linear-width Neural Networks
Prior Knowledge in Support Vector Kernels
Generalized Zero-Shot Learning with Deep Calibration Network
Exploring Forensic Dental Identification with Deep Learning
Increase Information Transfer Rates in BCI by CSP Extension to Multi-class
Object-Aware Regularization for Addressing Causal Confusion in Imitation Learning
Sample Complexity of Policy Search with Known Dynamics
On Neuronal Capacity
Stochastic Optimal Control Matching
Sparsity-Preserving Differentially Private Training of Large Embedding Models
Feature Importance Ranking for Deep Learning
Unbalanced Low-rank Optimal Transport Solvers
Communication-Efficient Algorithms for Statistical Optimization