yusuke1997/dblp-id-title huggingface dataset:
Query-Efficient Correlation Clustering with Noisy Oracle
Conditional Independence Testing with Heteroskedastic Data and Applications to Causal Discovery
Random Projections and Sampling Algorithms for Clustering of High-Dimensional Polygonal Curves
Link Prediction Based on Graph Neural Networks
Towards a robust experimental framework and benchmark for lifelong language learning
Alleviating Label Switching with Optimal Transport
Self-Imitation Learning via Generalized Lower Bound Q-learning
WebUOT-1M: Advancing Deep Underwater Object Tracking with A Million-Scale Benchmark
Isometric Quotient Variational Auto-Encoders for Structure-Preserving Representation Learning
Convergence of No-Swap-Regret Dynamics in Self-Play
Functional Bilevel Optimization for Machine Learning
SEEV: Synthesis with Efficient Exact Verification for ReLU Neural Barrier Functions
Is the Bellman residual a bad proxy?
Quantum Embedding of Knowledge for Reasoning
Transitivity Recovering Decompositions: Interpretable and Robust Fine-Grained Relationships
Fed-CO 2 : Cooperation of Online and Offline Models for Severe Data Heterogeneity in Federated Learning
Learning to See Rotation and Dilation with a Hebb Rule
MG-Net: Learn to Customize QAOA with Circuit Depth Awareness
On the Recursive Teaching Dimension of VC Classes
Joint distribution optimal transportation for domain adaptation
Towards Visual Text Design Transfer Across Languages
Adversarial GLUE: A Multi-Task Benchmark for Robustness Evaluation of Language Models
Robust Reinforcement Learning from Corrupted Human Feedback
Robust Visual Reasoning via Language Guided Neural Module Networks
Spherical Frustum Sparse Convolution Network for LiDAR Point Cloud Semantic Segmentation
Generalization and Scaling in Reinforcement Learning
Algorithms and matching lower bounds for approximately-convex optimization
Rademacher Complexity Bounds for Non-I.I.D. Processes
CO-PILOT: COllaborative Planning and reInforcement Learning On sub-Task curriculum
Fast Bellman Updates for Wasserstein Distributionally Robust MDPs
When to Trust Your Simulator: Dynamics-Aware Hybrid Offline-and-Online Reinforcement Learning
Uncertainty-aware Fine-tuning of Segmentation Foundation Models
Minimization of Continuous Bethe Approximations: A Positive Variation
Song Learning in Birds
A normative theory of social conflict
Towards Understanding the Dynamics of Gaussian-Stein Variational Gradient Descent
A Micropower Analog VLSI HMM State Decoder for Wordspotting
Co-Validation: Using Model Disagreement on Unlabeled Data to Validate Classification Algorithms
Pontryagin Differentiable Programming: An End-to-End Learning and Control Framework
Global Guarantees for Blind Demodulation with Generative Priors
Resilient Constrained Learning
Creating Multi-Level Skill Hierarchies in Reinforcement Learning
Fair Performance Metric Elicitation
What Can ResNet Learn Efficiently, Going Beyond Kernels?
Equitable Stable Matchings in Quadratic Time
Meet in the Middle: A New Pre-training Paradigm
Scalable 3D Captioning with Pretrained Models
A Long N-step Surrogate Stage Reward for Deep Reinforcement Learning
Clustering data through an analogy to the Potts model
BiToD: A Bilingual Multi-Domain Dataset For Task-Oriented Dialogue Modeling
Online Influence Maximization under Linear Threshold Model
Projecting Markov Random Field Parameters for Fast Mixing
The Sample Complexity of Semi-Supervised Learning with Nonparametric Mixture Models
Doob's Lagrangian: A Sample-Efficient Variational Approach to Transition Path Sampling
Parallel Inference for Latent Dirichlet Allocation on Graphics Processing Units
Prune and distill: similar reformatting of image information along rat visual cortex and deep neural networks
Analog Cochlear Model for Multiresolution Speech Analysis
Object based Scene Representations using Fisher Scores of Local Subspace Projections
A Computational Model of Prefrontal Cortex Function
GSDF: 3DGS Meets SDF for Improved Neural Rendering and Reconstruction
Effective End-to-end Unsupervised Outlier Detection via Inlier Priority of Discriminative Network
Molecule Joint Auto-Encoding: Trajectory Pretraining with 2D and 3D Diffusion
Do Adversarially Robust ImageNet Models Transfer Better?
Predicting the Optimal Spacing of Study: A Multiscale Context Model of Memory
A Gradient Method for Multilevel Optimization
An Attractor Neural Network Model of Recall and Recognition
Bridging the Gap Between Value and Policy Based Reinforcement Learning
Enhancing CLIP with CLIP: Exploring Pseudolabeling for Limited-Label Prompt Tuning
Incremental Boosting Convolutional Neural Network for Facial Action Unit Recognition
Differential Entropic Clustering of Multivariate Gaussians
Understanding Global Feature Contributions With Additive Importance Measures
Era3D: High-Resolution Multiview Diffusion using Efficient Row-wise Attention
Sparse Weight Activation Training
Associative Learning via Inhibitory Search
A Bayesian Nonparametrics View into Deep Representations
Classifying Patterns of Visual Motion - a Neuromorphic Approach
Learnable Visual Markers
$\alpha$-ReQ : Assessing Representation Quality in Self-Supervised Learning by measuring eigenspectrum decay
Learning Manifolds with K-Means and K-Flats
Expressing an Image Stream with a Sequence of Natural Sentences
Convergence Properties of Some Spike-Triggered Analysis Techniques
Snap ML: A Hierarchical Framework for Machine Learning
Solver-in-the-Loop: Learning from Differentiable Physics to Interact with Iterative PDE-Solvers
Probabilistic Relational PCA
Slot-guided Volumetric Object Radiance Fields
FuseAnyPart: Diffusion-Driven Facial Parts Swapping via Multiple Reference Images
Active Bipartite Ranking
On Misinformation Containment in Online Social Networks
Multi-view Masked Contrastive Representation Learning for Endoscopic Video Analysis
Multilingual Spoken Words Corpus
Towards Understanding Why Lookahead Generalizes Better Than SGD and Beyond
Onset-based Sound Segmentation
A Computation and Communication Efficient Method for Distributed Nonconvex Problems in the Partial Participation Setting
Subgroup-based Rank-1 Lattice Quasi-Monte Carlo
DeepExposure: Learning to Expose Photos with Asynchronously Reinforced Adversarial Learning
pyKT: A Python Library to Benchmark Deep Learning based Knowledge Tracing Models
Information Directed Reward Learning for Reinforcement Learning
The g Factor: Relating Distributions on Features to Distributions on Images
Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, NeurIPS 2021, December 6-14, 2021, virtual
PaDeLLM-NER: Parallel Decoding in Large Language Models for Named Entity Recognition
Compressing Large Language Models using Low Rank and Low Precision Decomposition
Truthful High Dimensional Sparse Linear Regression
Online Optimization for Max-Norm Regularization
Optimizing over trained GNNs via symmetry breaking
Independent Component Analysis for Identification of Artifacts in Magnetoencephalographic Recordings
Double Pessimism is Provably Efficient for Distributionally Robust Offline Reinforcement Learning: Generic Algorithm and Robust Partial Coverage
Learning the Local Statistics of Optical Flow
DASCO: Dual-Generator Adversarial Support Constrained Offline Reinforcement Learning
A Trichotomy for Transductive Online Learning
CLOSURE: Assessing Systematic Generalization of CLEVR Models
Compositional Transformers for Scene Generation
Mitigating Forgetting in Online Continual Learning via Instance-Aware Parameterization
General Bounds on Bayes Errors for Regression with Gaussian Processes
A Theory for Neural Networks with Time Delays
A Dictionary Approach to Domain-Invariant Learning in Deep Networks
DropoutNet: Addressing Cold Start in Recommender Systems
Neural Networks for Density Estimation
PLUR: A Unifying, Graph-Based View of Program Learning, Understanding, and Repair
MicroAdam: Accurate Adaptive Optimization with Low Space Overhead and Provable Convergence
Stochastic Three-Composite Convex Minimization
On the Strong Correlation Between Model Invariance and Generalization
Hardness of parameter estimation in graphical models
Dynamical Wasserstein Barycenters for Time-series Modeling
GPEX, A Framework For Interpreting Artificial Neural Networks
Hyperparameters Evidence and Generalisation for an Unrealisable Rule
Cluster-aware Semi-supervised Learning: Relational Knowledge Distillation Provably Learns Clustering
Explicit loss asymptotics in the gradient descent training of neural networks
Active Learning for Non-Parametric Regression Using Purely Random Trees
Modeling Saccadic Targeting in Visual Search
Controlled maximal variability along with reliable performance in recurrent neural networks
Efficient high dimensional maximum entropy modeling via symmetric partition functions
On the Adversarial Robustness of Out-of-distribution Generalization Models
Neuronal Gaussian Process Regression
Toward Better PAC-Bayes Bounds for Uniformly Stable Algorithms
Local Rules for Global MAP: When Do They Work ?
Unsupervised Deep Haar Scattering on Graphs
Efficient Resources Allocation for Markov Decision Processes
Evaluating alignment between humans and neural network representations in image-based learning tasks
Mutual-Information Regularized Multi-Agent Policy Iteration
Online Learning with a Hint
Structured Variational Inference in Continuous Cox Process Models
EZNAS: Evolving Zero-Cost Proxies For Neural Architecture Scoring
Learning Stochastic Majority Votes by Minimizing a PAC-Bayes Generalization Bound
Learning large-margin halfspaces with more malicious noise
Saving 100x Storage: Prototype Replay for Reconstructing Training Sample Distribution in Class-Incremental Semantic Segmentation
A Highly-Efficient Group Elastic Net Algorithm with an Application to Function-On-Scalar Regression
Cluster Trees on Manifolds
Approximate Secular Equations for the Cubic Regularization Subproblem
Finding Exemplars from Pairwise Dissimilarities via Simultaneous Sparse Recovery
A/B Testing for Recommender Systems in a Two-sided Marketplace
Differentially Private Optimization with Sparse Gradients
Fully Neural Network based Model for General Temporal Point Processes
Throttling Poisson Processes
Revisiting Score Propagation in Graph Out-of-Distribution Detection
Exploring Diverse In-Context Configurations for Image Captioning
An Annealed Self-Organizing Map for Source Channel Coding
On the Computational Complexity of Private High-dimensional Model Selection
A Unified Framework for Rank-based Loss Minimization
Fast Pure Exploration via Frank-Wolfe
On the Power of SVD in the Stochastic Block Model
Deep Graph Pose: a semi-supervised deep graphical model for improved animal pose tracking
Fast and Balanced: Efficient Label Tree Learning for Large Scale Object Recognition
Learning Superpoint Graph Cut for 3D Instance Segmentation
DropBP: Accelerating Fine-Tuning of Large Language Models by Dropping Backward Propagation
Learning Path Distributions Using Nonequilibrium Diffusion Networks
Compacter: Efficient Low-Rank Hypercomplex Adapter Layers
Memory-oriented Decoder for Light Field Salient Object Detection
Adversarial Robustness of Streaming Algorithms through Importance Sampling
Beta-Negative Binomial Process and Exchangeable Random Partitions for Mixed-Membership Modeling
Estimating Training Data Influence by Tracing Gradient Descent
SOLQ: Segmenting Objects by Learning Queries
A Near-Optimal Best-of-Both-Worlds Algorithm for Online Learning with Feedback Graphs
Dynamics-regulated kinematic policy for egocentric pose estimation
Quo Vadis: Is Trajectory Forecasting the Key Towards Long-Term Multi-Object Tracking?
Addressing Spatial-Temporal Heterogeneity: General Mixed Time Series Analysis via Latent Continuity Recovery and Alignment
Putting An End to End-to-End: Gradient-Isolated Learning of Representations
Automatic Alignment of Local Representations
Efficient Adversarial Contrastive Learning via Robustness-Aware Coreset Selection
Instead of Rewriting Foreign Code for Machine Learning, Automatically Synthesize Fast Gradients
Deep Inverse Q-learning with Constraints
Learning to Search Efficiently in High Dimensions
Variational Information Maximisation for Intrinsically Motivated Reinforcement Learning
GC-Bench: An Open and Unified Benchmark for Graph Condensation
SEXNET: A Neural Network Identifies Sex From Human Faces
Constrained Optimization to Train Neural Networks on Critical and Under-Represented Classes
DynGFN: Towards Bayesian Inference of Gene Regulatory Networks with GFlowNets
Variational Flow Matching for Graph Generation
Label Noise in Adversarial Training: A Novel Perspective to Study Robust Overfitting
Diversity Enhanced Active Learning with Strictly Proper Scoring Rules
Detecting Errors and Estimating Accuracy on Unlabeled Data with Self-training Ensembles
Parallel analog VLSI architectures for computation of heading direction and time-to-contact
SafeBench: A Benchmarking Platform for Safety Evaluation of Autonomous Vehicles
OLIVES Dataset: Ophthalmic Labels for Investigating Visual Eye Semantics
Optimization Principles for the Neural Code
Online Performative Gradient Descent for Learning Nash Equilibria in Decision-Dependent Games
How to Dynamically Merge Markov Decision Processes
Learning Multi-channel Deep Feature Representations for Face Recognition
SSAL: Synergizing between Self-Training and Adversarial Learning for Domain Adaptive Object Detection
Graph Classification via Reference Distribution Learning: Theory and Practice
Honesty Is the Best Policy: Defining and Mitigating AI Deception
Efficient Multiscale Sampling from Products of Gaussian Mixtures
Spatiotemporal Joint Filter Decomposition in 3D Convolutional Neural Networks
Synergy-of-Experts: Collaborate to Improve Adversarial Robustness
Margins are Insufficient for Explaining Gradient Boosting
Regularized Anderson Acceleration for Off-Policy Deep Reinforcement Learning
Hierarchical Uncertainty Exploration via Feedforward Posterior Trees
Data driven estimation of Laplace-Beltrami operator
Hyper-Graph-Network Decoders for Block Codes
From voxels to pixels and back: Self-supervision in natural-image reconstruction from fMRI
Region-based Segmentation and Object Detection
NL4Opt Competition: Formulating Optimization Problems Based on Their Natural Language Descriptions
CryptoGCN: Fast and Scalable Homomorphically Encrypted Graph Convolutional Network Inference
DRONE: Data-aware Low-rank Compression for Large NLP Models
A time-resolved theory of information encoding in recurrent neural networks
ALI-Agent: Assessing LLMs' Alignment with Human Values via Agent-based Evaluation
Adversarial robustness via robust low rank representations
Self-Supervised Deep Learning on Point Clouds by Reconstructing Space
AniFaceGAN: Animatable 3D-Aware Face Image Generation for Video Avatars
Posterior Network: Uncertainty Estimation without OOD Samples via Density-Based Pseudo-Counts
Fast Convergence of Natural Gradient Descent for Over-Parameterized Neural Networks
Learning Deep Attribution Priors Based On Prior Knowledge
(Not) Bounding the True Error
Theory of matching pursuit
Expected Improvement for Contextual Bandits
GNNExplainer: Generating Explanations for Graph Neural Networks
ZSC-Eval: An Evaluation Toolkit and Benchmark for Multi-agent Zero-shot Coordination
Cascaded Dilated Dense Network with Two-step Data Consistency for MRI Reconstruction
AutoML Two-Sample Test
Exact Gaussian Processes on a Million Data Points
Survival Permanental Processes for Survival Analysis with Time-Varying Covariates
SnapBoost: A Heterogeneous Boosting Machine
STLnet: Signal Temporal Logic Enforced Multivariate Recurrent Neural Networks
Learning Signal-Agnostic Manifolds of Neural Fields
Zero-Resource Knowledge-Grounded Dialogue Generation
Mind the Gap: A Generative Approach to Interpretable Feature Selection and Extraction
Wasserstein Distances for Stereo Disparity Estimation
Stochastic Composite Mirror Descent: Optimal Bounds with High Probabilities
Learning Generative Vision Transformer with Energy-Based Latent Space for Saliency Prediction
Contextual Reserve Price Optimization in Auctions via Mixed Integer Programming
Active Learning-Based Species Range Estimation
Rapidly Adapting Artificial Neural Networks for Autonomous Navigation
Improving Network Models and Algorithmic Tricks: Preface
A Finite-Particle Convergence Rate for Stein Variational Gradient Descent
Slice-100K: A Multimodal Dataset for Extrusion-based 3D Printing
Conflict-Averse Gradient Descent for Multi-task learning
On Single Source Robustness in Deep Fusion Models
D2C: Diffusion-Decoding Models for Few-Shot Conditional Generation
Classifying Facial Action
Regret Bounds for Non-decomposable Metrics with Missing Labels
Stochastic Normalizing Flows
Maximum-Entropy Adversarial Data Augmentation for Improved Generalization and Robustness
Reinforcement Learning with Combinatorial Actions: An Application to Vehicle Routing
Backpropagation and Its Application to Handwritten Signature Verification
Nonparametric estimation of continuous DPPs with kernel methods
ConflictBank: A Benchmark for Evaluating the Influence of Knowledge Conflicts in LLMs
Reinforcement Learning with Logarithmic Regret and Policy Switches
A Latent Feature Analysis of the Neural Representation of Conceptual Knowledge
Online Learning of Assignments
A Causal Framework for Decomposing Spurious Variations
InterDreamer: Zero-Shot Text to 3D Dynamic Human-Object Interaction
Toward Global Convergence of Gradient EM for Over-Paramterized Gaussian Mixture Models
Prompt Optimization with EASE? Efficient Ordering-aware Automated Selection of Exemplars
Continuous Regularized Wasserstein Barycenters
Lower Bounds on Metropolized Sampling Methods for Well-Conditioned Distributions
Region-specific Diffeomorphic Metric Mapping
Improved Network Robustness with Adversary Critic
Simplify and Robustify Negative Sampling for Implicit Collaborative Filtering
On the Robustness of Graph Neural Diffusion to Topology Perturbations
Differential Properties of Sinkhorn Approximation for Learning with Wasserstein Distance
Scalable Neural Video Representations with Learnable Positional Features
Multivariate Triangular Quantile Maps for Novelty Detection
On Exact Computation with an Infinitely Wide Neural Net
WISE: Rethinking the Knowledge Memory for Lifelong Model Editing of Large Language Models
Optimality of Message-Passing Architectures for Sparse Graphs
Nature-Inspired Local Propagation
A Tractable Approximation to Optimal Point Process Filtering: Application to Neural Encoding
WorldCoder, a Model-Based LLM Agent: Building World Models by Writing Code and Interacting with the Environment
Connectionist Speaker Normalization with Generalized Resource Allocating Networks
Answering Complex Causal Queries With the Maximum Causal Set Effect
Posted Pricing and Dynamic Prior-independent Mechanisms with Value Maximizers
Mechanic: A Learning Rate Tuner
Efficient Architecture Search for Diverse Tasks
Gradient-free Decoder Inversion in Latent Diffusion Models
PolyDiffuse: Polygonal Shape Reconstruction via Guided Set Diffusion Models
Stability and Generalization Analysis of Gradient Methods for Shallow Neural Networks
The EURO Meets NeurIPS 2022 Vehicle Routing Competition
Going Beyond Linear Transformers with Recurrent Fast Weight Programmers
FedGMKD: An Efficient Prototype Federated Learning Framework through Knowledge Distillation and Discrepancy-Aware Aggregation
Thinned random measures for sparse graphs with overlapping communities
A Group-Theoretic Framework for Data Augmentation
Variational Bayesian Unlearning
OTLDA: A Geometry-aware Optimal Transport Approach for Topic Modeling
Achieving Constant Regret in Linear Markov Decision Processes
Continuous-time Analysis of Anchor Acceleration
The Parameterized Complexity of Cascading Portfolio Scheduling
Max-margin classification of incomplete data
EgoSchema: A Diagnostic Benchmark for Very Long-form Video Language Understanding
NeuroGF: A Neural Representation for Fast Geodesic Distance and Path Queries
Debiased and Denoised Entity Recognition from Distant Supervision
Online Iterative Reinforcement Learning from Human Feedback with General Preference Model
Coresets via Bilevel Optimization for Continual Learning and Streaming
Conditional score-based diffusion models for Bayesian inference in infinite dimensions
Field-wise Learning for Multi-field Categorical Data
Baby Intuitions Benchmark (BIB): Discerning the goals, preferences, and actions of others
Hierarchical Federated Learning with Multi-Timescale Gradient Correction
Multi-Class Learning: From Theory to Algorithm
Training Transitive and Commutative Multimodal Transformers with LoReTTa
Nearly Minimax Optimal Reinforcement Learning for Discounted MDPs
Hypothesis Selection with Memory Constraints
Finite-Time Regret of Thompson Sampling Algorithms for Exponential Family Multi-Armed Bandits
Coded Distributed Computing for Inverse Problems
PLANS: Neuro-Symbolic Program Learning from Videos
Adaptive Density Estimation for Generative Models
Replacing Rewards with Examples: Example-Based Policy Search via Recursive Classification
Masked Space-Time Hash Encoding for Efficient Dynamic Scene Reconstruction
How Does it Sound?
TSGM: A Flexible Framework for Generative Modeling of Synthetic Time Series
Approximating the Permanent by Sampling from Adaptive Partitions
Learning Label Trees for Probabilistic Modelling of Implicit Feedback
Posterior Consistency of the Silverman g-prior in Bayesian Model Choice
Evaluating Neuron Interpretation Methods of NLP Models
Residual Force Control for Agile Human Behavior Imitation and Extended Motion Synthesis
Understanding Robust Learning through the Lens of Representation Similarities
Maximum Entropy Inverse Reinforcement Learning of Diffusion Models with Energy-Based Models
Targeting EEG/LFP Synchrony with Neural Nets
Rethinking Memory and Communication Costs for Efficient Data Parallel Training of Large Language Models
Immiscible Diffusion: Accelerating Diffusion Training with Noise Assignment
Zero-to-Hero: Enhancing Zero-Shot Novel View Synthesis via Attention Map Filtering
Algebraic Positional Encodings
What do row and column marginals reveal about your dataset?
Generalizable Lightweight Proxy for Robust NAS against Diverse Perturbations
A Constructive RBF Network for Writer Adaptation
PiRank: Scalable Learning To Rank via Differentiable Sorting
Recruitment Strategies That Take a Chance
Individuation, Identification and Object Discovery
A Switched Gaussian Process for Estimating Disparity and Segmentation in Binocular Stereo
SynRS3D: A Synthetic Dataset for Global 3D Semantic Understanding from Monocular Remote Sensing Imagery
Global Gated Mixture of Second-order Pooling for Improving Deep Convolutional Neural Networks
Online Minimax Multiobjective Optimization: Multicalibeating and Other Applications
Near-Optimal Correlation Clustering with Privacy
Range Image Restoration Using Mean Field Annealing
SemFlow: Binding Semantic Segmentation and Image Synthesis via Rectified Flow
A Debiased MDI Feature Importance Measure for Random Forests
Fast-Slow Recurrent Neural Networks
Keeping Your Distance: Solving Sparse Reward Tasks Using Self-Balancing Shaped Rewards
Inferring Algorithmic Patterns with Stack-Augmented Recurrent Nets
Bayesian decision-making under misspecified priors with applications to meta-learning
CryoGEM: Physics-Informed Generative Cryo-Electron Microscopy
Semi-supervised Active Linear Regression
Recurrent Registration Neural Networks for Deformable Image Registration
Object Goal Navigation using Goal-Oriented Semantic Exploration
Perturbation Theory for the Information Bottleneck
Design Space for Graph Neural Networks
Nested Variational Inference
Noise-Adaptive Thompson Sampling for Linear Contextual Bandits
Linear Concepts and Hidden Variables: An Empirical Study
Hybrid Variance-Reduced SGD Algorithms For Minimax Problems with Nonconvex-Linear Function
DiffuPac: Contextual Mimicry in Adversarial Packets Generation via Diffusion Model
DVSOD: RGB-D Video Salient Object Detection
MetaReg: Towards Domain Generalization using Meta-Regularization
MLLMGuard: A Multi-dimensional Safety Evaluation Suite for Multimodal Large Language Models
Sequence Model Imitation Learning with Unobserved Contexts