yusuke1997/dblp-id-title huggingface dataset:
Robust Learning of Optimal Auctions
Last-iterate Convergence in Extensive-Form Games
A Market Framework for Eliciting Private Data
Rethinking Calibration of Deep Neural Networks: Do Not Be Afraid of Overconfidence
Temporal Coherency based Criteria for Predicting Video Frames using Deep Multi-stage Generative Adversarial Networks
Self-attention with Functional Time Representation Learning
Mars: Situated Inductive Reasoning in an Open-World Environment
Decoupled Context Processing for Context Augmented Language Modeling
Tolerant Algorithms for Learning with Arbitrary Covariate Shift
Message-Passing for Approximate MAP Inference with Latent Variables
Unsupervised Point Cloud Completion and Segmentation by Generative Adversarial Autoencoding Network
On the Existence of The Adversarial Bayes Classifier
RECKONING: Reasoning through Dynamic Knowledge Encoding
Evaluating the statistical significance of biclusters
Understanding the Role of Momentum in Stochastic Gradient Methods
Algorithmic Luckiness
Spectral Bounds for Sparse PCA: Exact and Greedy Algorithms
Active Regression by Stratification
RegExplainer: Generating Explanations for Graph Neural Networks in Regression Tasks
Multi-task Additive Models for Robust Estimation and Automatic Structure Discovery
Self-Paced Deep Reinforcement Learning
Sharing Features among Dynamical Systems with Beta Processes
Benchmarking Non-Parametric Statistical Tests
ET-Flow: Equivariant Flow-Matching for Molecular Conformer Generation
WITRAN: Water-wave Information Transmission and Recurrent Acceleration Network for Long-range Time Series Forecasting
Beyond Separability: Analyzing the Linear Transferability of Contrastive Representations to Related Subpopulations
Stylebreeder: Exploring and Democratizing Artistic Styles through Text-to-Image Models
WebQA: A Multimodal Multihop NeurIPS Challenge
Compact EEPROM-based Weight Functions
Flexible Context-Driven Sensory Processing in Dynamical Vision Models
Sparse Approximate Conic Hulls
Addressing Hidden Confounding with Heterogeneous Observational Datasets for Recommendation
Collaboratively Learning Linear Models with Structured Missing Data
Mean Field Approach to a Probabilistic Model in Information Retrieval
Image Recognition in Context: Application to Microscopic Urinalysis
Improvements on Uncertainty Quantification for Node Classification via Distance Based Regularization
Statistical Debugging of Sampled Programs
Provable Advantage of Curriculum Learning on Parity Targets with Mixed Inputs
Classification-Based Causality Detection in Time Series
A Spectral Approach to Item Response Theory
Dense Correspondences between Human Bodies via Learning Transformation Synchronization on Graphs
Surrogate Objectives for Batch Policy Optimization in One-step Decision Making
Differentially Private Covariance Estimation
Post training 4-bit quantization of convolutional networks for rapid-deployment
Scale Equivariant Graph Metanetworks
The Dynamic Beamformer
Scalable Bayesian GPFA with automatic relevance determination and discrete noise models
Fine-tuning language models to find agreement among humans with diverse preferences
InsNet: An Efficient, Flexible, and Performant Insertion-based Text Generation Model
Clustering Effect of Adversarial Robust Models
Globally solving the Gromov-Wasserstein problem for point clouds in low dimensional Euclidean spaces
Efficient Meta Neural Heuristic for Multi-Objective Combinatorial Optimization
Learning to Discuss Strategically: A Case Study on One Night Ultimate Werewolf
Model Preserving Compression for Neural Networks
Prismatic Algorithm for Discrete D.C. Programming Problem
DISCO-10M: A Large-Scale Music Dataset
Lookback Prophet Inequalities
Hessian-free Optimization for Learning Deep Multidimensional Recurrent Neural Networks
TaiSu: A 166M Large-scale High-Quality Dataset for Chinese Vision-Language Pre-training
Entropic Graph Regularization in Non-Parametric Semi-Supervised Classification
A new metric on the manifold of kernel matrices with application to matrix geometric means
Bayesian Optimization of Function Networks
Fair, Polylog-Approximate Low-Cost Hierarchical Clustering
Transform Once: Efficient Operator Learning in Frequency Domain
Variational Learning for Recurrent Spiking Networks
Limitations of Self-organizing Maps for Vector Quantization and Multidimensional Scaling
A Dynamical Moedl of Context Dependencies for the Vestibulo-Ocular Reflex
Discovering Structure in Continuous Variables Using Bayesian Networks
Stochastic Continuous Greedy ++: When Upper and Lower Bounds Match
Learning Temporally Persistent Hierarchical Representations
Preference Completion from Partial Rankings
Polynomial Cost of Adaptation for X-Armed Bandits
Grouping Contours by Iterated Pairing Networks
Beating Adversarial Low-Rank MDPs with Unknown Transition and Bandit Feedback
Deep Smoothing of the Implied Volatility Surface
Fast Iterative Kernel PCA
Imprecise Label Learning: A Unified Framework for Learning with Various Imprecise Label Configurations
Adaptive Stochastic Optimization: From Sets to Paths
Functional Renyi Differential Privacy for Generative Modeling
Generative Local Metric Learning for Kernel Regression
ShapeFlow: Learnable Deformation Flows Among 3D Shapes
Not All Actions Are Equal: Learning to Stop in Language-Grounded Urban Navigation
SGLang: Efficient Execution of Structured Language Model Programs
Reducing the Rank in Relational Factorization Models by Including Observable Patterns
What matters when building vision-language models?
Understanding Representation of Deep Equilibrium Models from Neural Collapse Perspective
Convex Two-Layer Modeling with Latent Structure
SNEkhorn: Dimension Reduction with Symmetric Entropic Affinities
Balancing Risk and Reward: A Batched-Bandit Strategy for Automated Phased Release
Unsupervised Learning under Latent Label Shift
Outcome-Driven Reinforcement Learning via Variational Inference
Minimax Classifier with Box Constraint on the Priors
Local Probability Propagation for Factor Analysis
Deep Supervised Summarization: Algorithm and Application to Learning Instructions
Tracing Hyperparameter Dependencies for Model Parsing via Learnable Graph Pooling Network
Self-Instantiated Recurrent Units with Dynamic Soft Recursion
Analog Computation at a Critical Point
Convergence-Rate-Matching Discretization of Accelerated Optimization Flows Through Opportunistic State-Triggered Control
SEEDS: Exponential SDE Solvers for Fast High-Quality Sampling from Diffusion Models
LG-CAV: Train Any Concept Activation Vector with Language Guidance
Automating Dataset Updates Towards Reliable and Timely Evaluation of Large Language Models
SALSA VERDE: a machine learning attack on LWE with sparse small secrets
Advances in Neural Information Processing Systems 18 [Neural Information Processing Systems, NIPS 2005, December 5-8, 2005, Vancouver, British Columbia, Canada]
High Performance Neural Net Simulation on a Multiprocessor System with Intelligent Communication
Bayesian Domain Adaptation with Gaussian Mixture Domain-Indexing
Causal Interpretation of Self-Attention in Pre-Trained Transformers
A Theoretical Analysis of Optimistic Proximal Policy Optimization in Linear Markov Decision Processes
T2Vs Meet VLMs: A Scalable Multimodal Dataset for Visual Harmfulness Recognition
Hierarchies of Adaptive Experts
Large-Scale Wasserstein Gradient Flows
Implicit Neural Representations with Levels-of-Experts
Fourier Spectrum Discrepancies in Deep Network Generated Images
The Neural Hawkes Process: A Neurally Self-Modulating Multivariate Point Process
Statistically Meaningful Approximation: a Case Study on Approximating Turing Machines with Transformers
ComBack: A Versatile Dataset for Enhancing Compiler Backend Development Efficiency
Bidirectional Convolutional Poisson Gamma Dynamical Systems
Exploring Context Window of Large Language Models via Decomposed Positional Vectors
UNIT: Unifying Image and Text Recognition in One Vision Encoder
When does return-conditioned supervised learning work for offline reinforcement learning?
High-Fidelity Audio Compression with Improved RVQGAN
Unsupervised Cross-Modal Alignment of Speech and Text Embedding Spaces
X-Ray: A Sequential 3D Representation For Generation
The Distribution Family of Similarity Distances
GENESIS: A System for Simulating Neural Networks
Learning From Small Samples: An Analysis of Simple Decision Heuristics
Asymptotic optimality of adaptive importance sampling
Adaptive Low-Complexity Sequential Inference for Dirichlet Process Mixture Models
Global Lyapunov functions: a long-standing open problem in mathematics, with symbolic transformers
Permute-and-Flip: A new mechanism for differentially private selection
Diffusion Policies Creating a Trust Region for Offline Reinforcement Learning
A Mathematical Model For Optimal Decisions In A Representative Democracy
Planning for Markov Decision Processes with Sparse Stochasticity
Predictive Uncertainty Estimation via Prior Networks
SafeDICE: Offline Safe Imitation Learning with Non-Preferred Demonstrations
Alternating Gradient Descent and Mixture-of-Experts for Integrated Multimodal Perception
Greedy and Random Quasi-Newton Methods with Faster Explicit Superlinear Convergence
Asynchronous Actor-Critic for Multi-Agent Reinforcement Learning
Memory Efficient Continual Learning with Transformers
On the convergence of policy gradient methods to Nash equilibria in general stochastic games
Cross-Modal Mapping for Generalized Zero-Shot Learning by Soft-Labeling
Rethinking Alignment in Video Super-Resolution Transformers
DTGB: A Comprehensive Benchmark for Dynamic Text-Attributed Graphs
Hypothesis Testing the Circuit Hypothesis in LLMs
EigenNet: A Bayesian hybrid of generative and conditional models for sparse learning
Recurrent Video Restoration Transformer with Guided Deformable Attention
Stochastic Concept Bottleneck Models
Contextual Bandits with Knapsacks for a Conversion Model
A Differential Equation for Modeling Nesterov's Accelerated Gradient Method: Theory and Insights
Risk Monotonicity in Statistical Learning
Deep Generative Model for Periodic Graphs
Scheduling Straight-Line Code Using Reinforcement Learning and Rollouts
AdANNS: A Framework for Adaptive Semantic Search
Automatic Acquisition and Efficient Representation of Syntactic Structures
Change Point Detection via Multivariate Singular Spectrum Analysis
MAmmoTH2: Scaling Instructions from the Web
ProtoVAE: A Trustworthy Self-Explainable Prototypical Variational Model
MAViL: Masked Audio-Video Learners
MeshSDF: Differentiable Iso-Surface Extraction
Shuffling Gradient-Based Methods for Nonconvex-Concave Minimax Optimization
Semi-Supervised Learning with Adversarially Missing Label Information
Analog VLSI Model of Intersegmental Coordination with Nearest-Neighbor Coupling
CSI: Novelty Detection via Contrastive Learning on Distributionally Shifted Instances
Image Understanding Makes for A Good Tokenizer for Image Generation
A Predictive Switching Model of Cerebellar Movement Control
BigBio: A Framework for Data-Centric Biomedical Natural Language Processing
Bridging The Gap between Low-rank and Orthogonal Adaptation via Householder Reflection Adaptation
Collaborative Linear Bandits with Adversarial Agents: Near-Optimal Regret Bounds
Fitted Q-iteration by Advantage Weighted Regression
Reinforcement Learning with Adaptive Regularization for Safe Control of Critical Systems
A Temporal Kernel-Based Model for Tracking Hand Movements from Neural Activities
TokenMixup: Efficient Attention-guided Token-level Data Augmentation for Transformers
Generalized Cross Entropy Loss for Training Deep Neural Networks with Noisy Labels
Generalized Proximal Policy Optimization with Sample Reuse
A Theoretical Study on Solving Continual Learning
Topological obstruction to the training of shallow ReLU neural networks
Comparing the Effects of Different Weight Distributions on Finding Sparse Representations
AsEP: Benchmarking Deep Learning Methods for Antibody-specific Epitope Prediction
Word Features for Latent Dirichlet Allocation
Does GNN Pretraining Help Molecular Representation?
Constrained Reinforcement Learning Has Zero Duality Gap
NxMTransformer: Semi-Structured Sparsification for Natural Language Understanding via ADMM
Plasticity of Center-Surround Opponent Receptive Fields in Real and Artificial Neural Systems of Vision
High-dimensional limit theorems for SGD: Effective dynamics and critical scaling
Accelerated Mini-Batch Stochastic Dual Coordinate Ascent
Hub-Pathway: Transfer Learning from A Hub of Pre-trained Models
LTMD: Learning Improvement of Spiking Neural Networks with Learnable Thresholding Neurons and Moderate Dropout
Correlated random features for fast semi-supervised learning
A Best-of-Both-Worlds Algorithm for Bandits with Delayed Feedback
Completing State Representations using Spectral Learning
Energy-Based Sliced Wasserstein Distance
Strongly Incremental Constituency Parsing with Graph Neural Networks
Gauge Equivariant Transformer
Fractal Landscapes in Policy Optimization
Revisiting the Minimalist Approach to Offline Reinforcement Learning
Minkowski-r Back-Propagation: Learning in Connectionist Models with Non-Euclidian Error Signals
Gaussian Graph Network: Learning Efficient and Generalizable Gaussian Representations from Multi-view Images
Densely connected normalizing flows
A Guide Through the Zoo of Biased SGD
SHOT: Suppressing the Hessian along the Optimization Trajectory for Gradient-Based Meta-Learning
LithoBench: Benchmarking AI Computational Lithography for Semiconductor Manufacturing
Implicitly Constrained Gaussian Process Regression for Monocular Non-Rigid Pose Estimation
Spontaneous symmetry breaking in generative diffusion models
Robust Predictable Control
Escape saddle points by a simple gradient-descent based algorithm
Diffusion-LM Improves Controllable Text Generation
Make-An-Agent: A Generalizable Policy Network Generator with Behavior-Prompted Diffusion
DiMSUM: Diffusion Mamba - A Scalable and Unified Spatial-Frequency Method for Image Generation
Bandits with Feedback Graphs and Switching Costs
Expressivity-Preserving GNN Simulation
Large language models implicitly learn to straighten neural sentence trajectories to construct a predictive representation of natural language
Semi-Supervised Partial Label Learning via Confidence-Rated Margin Maximization
Online Non-Convex Optimization with Imperfect Feedback
Decoding the Enigma: Benchmarking Humans and AIs on the Many Facets of Working Memory
CSLP-AE: A Contrastive Split-Latent Permutation Autoencoder Framework for Zero-Shot Electroencephalography Signal Conversion
Synaptic Weight Noise During MLP Learning Enhances Fault-Tolerance, Generalization and Learning Trajectory
Maximum likelihood trajectories for continuous-time Markov chains
Improving Contrastive Learning on Imbalanced Data via Open-World Sampling
Cross Species Expression Analysis using a Dirichlet Process Mixture Model with Latent Matchings
No-Regret Learning Dynamics for Extensive-Form Correlated Equilibrium
On Blame Attribution for Accountable Multi-Agent Sequential Decision Making
Recommender Systems with Generative Retrieval
Hamiltonian descent for composite objectives
Neural Network - Gaussian Mixture Hybrid for Speech Recognition or Density Estimation
REAL-2019: Robot open-Ended Autonomous Learning competition
Generative Status Estimation and Information Decoupling for Image Rain Removal
Approximate Bayesian Inference for a Mechanistic Model of Vesicle Release at a Ribbon Synapse
Structured Sparse Regression via Greedy Hard Thresholding
Text-Aware Diffusion for Policy Learning
Unified Speech Recognition: A Single Model for Auditory, Visual, and Audiovisual Inputs
KNG: The K-Norm Gradient Mechanism
OSOA: One-Shot Online Adaptation of Deep Generative Models for Lossless Compression
Sequential Neural Processes
Efficient Adaptation of Large Vision Transformer via Adapter Re-Composing
Near-Optimal Distributionally Robust Reinforcement Learning with General $L_p$ Norms
Contrastive Learning Using Spectral Methods
Privacy-preserving logistic regression
Online Learning of Delayed Choices
Analysis of Distributed Representation of Constituent Structure in Connectionist Systems
On Computational Power and the Order-Chaos Phase Transition in Reservoir Computing
Ensemble and Modular Approaches for Face Detection: A Comparison
Neural Control for Rolling Mills: Incorporating Domain Theories to Overcome Data Deficiency
On the Constrained Time-Series Generation Problem
Debiasing Graph Neural Networks via Learning Disentangled Causal Substructure
Stability and Generalization of Bilevel Programming in Hyperparameter Optimization
Trial matching: capturing variability with data-constrained spiking neural networks
DARNet: Dual Attention Refinement Network with Spatiotemporal Construction for Auditory Attention Detection
Coneheads: Hierarchy Aware Attention
RETRIEVE: Coreset Selection for Efficient and Robust Semi-Supervised Learning
Uncertainty Quantification over Graph with Conformalized Graph Neural Networks
FastGRNN: A Fast, Accurate, Stable and Tiny Kilobyte Sized Gated Recurrent Neural Network
Scaling Retrieval-Based Language Models with a Trillion-Token Datastore
Counterfactual Fairness by Combining Factual and Counterfactual Predictions
Stochastic Optimization Algorithms for Instrumental Variable Regression with Streaming Data
Benchmarking Structural Inference Methods for Interacting Dynamical Systems with Synthetic Data
Reinforcement Learning for Mixed Open-loop and Closed-loop Control
GenDeR: A Generic Diversified Ranking Algorithm
Dense Interspecies Face Embedding
Solving the multi-way matching problem by permutation synchronization
HQA-Attack: Toward High Quality Black-Box Hard-Label Adversarial Attack on Text
Parallelizing MCMC with Random Partition Trees
Reconstruction of Sparse Circuits Using Multi-neuronal Excitation (RESCUME)
Feature Selection by Maximum Marginal Diversity
The Neural MMO Platform for Massively Multiagent Research
Uncertainty Sampling is Preconditioned Stochastic Gradient Descent on Zero-One Loss
Regularized Distance Metric Learning: Theory and Algorithm
Set Prediction in the Latent Space
Unsupervised Representation Learning by Invariance Propagation
Efficient Multi-agent Communication via Self-supervised Information Aggregation
An ideal observer model for identifying the reference frame of objects
Linear readout from a neural population with partial correlation data
TOHAN: A One-step Approach towards Few-shot Hypothesis Adaptation
Shallow RNN: Accurate Time-series Classification on Resource Constrained Devices
IRM - when it works and when it doesn't: A test case of natural language inference
CircleGAN: Generative Adversarial Learning across Spherical Circles
Uncertainty-Aware Instance Reweighting for Off-Policy Learning
Partial Counterfactual Identification of Continuous Outcomes with a Curvature Sensitivity Model
A Dynamical Model of Priming and Repetition Blindness
Correlation in Extensive-Form Games: Saddle-Point Formulation and Benchmarks
DiffPO: A causal diffusion model for learning distributions of potential outcomes
Deep Direct Likelihood Knockoffs
Recovering Articulated Model Topology from Observed Rigid Motion
Locally Uniform Comparison Image Descriptor
WaveBound: Dynamic Error Bounds for Stable Time Series Forecasting
Learning with SGD and Random Features
Spike Sorting: Bayesian Clustering of Non-Stationary Data
GNNEvaluator: Evaluating GNN Performance On Unseen Graphs Without Labels
Leap-Of-Thought: Teaching Pre-Trained Models to Systematically Reason Over Implicit Knowledge
Policy-Conditioned Uncertainty Sets for Robust Markov Decision Processes
Target-Guided Adversarial Point Cloud Transformer Towards Recognition Against Real-world Corruptions
Structural Pruning for Diffusion Models
DIFFRAC: a discriminative and flexible framework for clustering
Learning from Few Samples: Transformation-Invariant SVMs with Composition and Locality at Multiple Scales
A Rate Distortion Approach for Semi-Supervised Conditional Random Fields
Self-Supervised Relational Reasoning for Representation Learning
Conformal Frequency Estimation with Sketched Data
Neural Similarity Learning
Teacher Forcing Recovers Reward Functions for Text Generation
A Winner-Take-All Circuit with Controllable Soft Max Property
Pushing the Limits of Narrow Precision Inferencing at Cloud Scale with Microsoft Floating Point
Projection onto A Nonnegative Max-Heap
Observational Scaling Laws and the Predictability of Langauge Model Performance
Multi-resolution Spectral Coherence for Graph Generation with Score-based Diffusion
Supervised Exponential Family Principal Component Analysis via Convex Optimization
Can Neural Networks Do Better Than the Vapnik-Chervonenkis Bounds?
Non-Stationary Bandits with Auto-Regressive Temporal Dependency
Adversarial Schrödinger Bridge Matching
Understanding and Mitigating Copying in Diffusion Models
Utilizing lime: Asynchronous Binding
Maximizing acquisition functions for Bayesian optimization
Qualitative Mechanism Independence
An Analog Implementation of the Constant Average Statistics Constraint For Sensor Calibration
Fast Best-of-N Decoding via Speculative Rejection
Pelee: A Real-Time Object Detection System on Mobile Devices
Test Where Decisions Matter: Importance-driven Testing for Deep Reinforcement Learning
Multi-Step Budgeted Bayesian Optimization with Unknown Evaluation Costs
Robust Optimization for Multilingual Translation with Imbalanced Data
Generating Accurate and Diverse Members of a Neural-Network Ensemble
LoCoOp: Few-Shot Out-of-Distribution Detection via Prompt Learning
A Tighter Bound for Graphical Models
A Bridging Framework for Model Optimization and Deep Propagation
Critical Lines in Symmetry of Mixture Models and its Application to Component Splitting
Optimal Brain Surgeon: Extensions and performance comparison
Exploiting the Structure: Stochastic Gradient Methods Using Raw Clusters
Bayesian Multi-type Mean Field Multi-agent Imitation Learning
Causal Inference with Noisy and Missing Covariates via Matrix Factorization
COVE: Unleashing the Diffusion Feature Correspondence for Consistent Video Editing
Learning from Failure: De-biasing Classifier from Biased Classifier
Avoiding Imposters and Delinquents: Adversarial Crowdsourcing and Peer Prediction
A Generalized Bradley-Terry Model: From Group Competition to Individual Skill
Learned in Translation: Contextualized Word Vectors
DisDiff: Unsupervised Disentanglement of Diffusion Probabilistic Models
When Do Neural Networks Outperform Kernel Methods?
Auxiliary Losses for Learning Generalizable Concept-based Models
ABC: Auxiliary Balanced Classifier for Class-imbalanced Semi-supervised Learning
Sample-Efficient Constrained Reinforcement Learning with General Parameterization
Learning Causal Effects via Weighted Empirical Risk Minimization
Blind Regression: Nonparametric Regression for Latent Variable Models via Collaborative Filtering
Online Prediction on Large Diameter Graphs
ReF-LDM: A Latent Diffusion Model for Reference-based Face Image Restoration
Exploiting Contextual Objects and Relations for 3D Visual Grounding
Discrete-state Continuous-time Diffusion for Graph Generation
Multi-effect Decompositions for Financial Data Modeling
Optimistic Gittins Indices
Improved Schemes for Episodic Memory-based Lifelong Learning
Adaptive SGD with Polyak stepsize and Line-search: Robust Convergence and Variance Reduction
Optimal Flow Matching: Learning Straight Trajectories in Just One Step
PersonalSum: A User-Subjective Guided Personalized Summarization Dataset for Large Language Models
Efficient Learning of Generative Models via Finite-Difference Score Matching
Terra: Imperative-Symbolic Co-Execution of Imperative Deep Learning Programs
ALGO: Synthesizing Algorithmic Programs with Generated Oracle Verifiers
Cross-Validation Estimates ISME
Tighter PAC-Bayes Bounds
Solving Most Systems of Random Quadratic Equations
A Modular Conditional Diffusion Framework for Image Reconstruction
U-Time: A Fully Convolutional Network for Time Series Segmentation Applied to Sleep Staging
Bootstrapping from Game Tree Search
Matrix Completion from Fewer Entries: Spectral Detectability and Rank Estimation
Necessary and Sufficient Geometries for Gradient Methods
Video Token Merging for Long Video Understanding
Delegated Classification