yusuke1997/dblp-id-title huggingface dataset:
Trading Personalization for Accuracy: Data Debugging in Collaborative Filtering
Few-Shot Data-Driven Algorithms for Low Rank Approximation
Learning Long-Term Crop Management Strategies with CyclesGym
Improving Diffusion Models for Inverse Problems using Manifold Constraints
Boosting with Spatial Regularization
Explore no more: Improved high-probability regret bounds for non-stochastic bandits
Recurrent Convolutional Neural Networks Learn Succinct Learning Algorithms
A Game-Theoretic Approach to Apprenticeship Learning
Understanding End-to-End Model-Based Reinforcement Learning Methods as Implicit Parameterization
Masking: A New Perspective of Noisy Supervision
Spike and slab variational Bayes for high dimensional logistic regression
Iterative Construction of Sparse Polynomial Approximations
Accuracy at the Top
Scalable Discriminative Learning for Natural Language Parsing and Translation
🏘️ ProcTHOR: Large-Scale Embodied AI Using Procedural Generation
Deep Network for the Integrated 3D Sensing of Multiple People in Natural Images
Zero-Shot Learning Through Cross-Modal Transfer
A Novel Gaussian Sum Smoother for Approximate Inference in Switching Linear Dynamical Systems
On the Variance of the Fisher Information for Deep Learning
Taming the Long Tail in Human Mobility Prediction
Conditional Diffusion Process for Inverse Halftoning
Aligning Audio-Visual Joint Representations with an Agentic Workflow
Unknown-Aware Domain Adversarial Learning for Open-Set Domain Adaptation
Flexpoint: An Adaptive Numerical Format for Efficient Training of Deep Neural Networks
No Train, all Gain: Self-Supervised Gradients Improve Deep Frozen Representations
Vript: A Video Is Worth Thousands of Words
Learning Parities with Neural Networks
Semialgebraic Representation of Monotone Deep Equilibrium Models and Applications to Certification
Probabilistic Movement Primitives
Improving GAN Training with Probability Ratio Clipping and Sample Reweighting
A new perspective on building efficient and expressive 3D equivariant graph neural networks
A Regularized Conditional GAN for Posterior Sampling in Image Recovery Problems
Fast Certified Robust Training with Short Warmup
Accelerated Variational Dirichlet Process Mixtures
Look More but Care Less in Video Recognition
Hierarchical Recurrent Neural Networks for Long-Term Dependencies
Gradient Flow Independent Component Analysis in Micropower VLSI
Local Spatiotemporal Representation Learning for Longitudinally-consistent Neuroimage Analysis
Incentives in Private Collaborative Machine Learning
MST: Masked Self-Supervised Transformer for Visual Representation
Incremental A*
AutoTimes: Autoregressive Time Series Forecasters via Large Language Models
GraphAdapter: Tuning Vision-Language Models With Dual Knowledge Graph
Subset Selection and Summarization in Sequential Data
iSplit LBI: Individualized Partial Ranking with Ties via Split LBI
GDS: Gradient Descent Generation of Symbolic Classification Rules
A Simple Cache Model for Image Recognition
Collaborative Learning by Detecting Collaboration Partners
Uniqueness of the SVM Solution
TA-GATES: An Encoding Scheme for Neural Network Architectures
Adaptive Scaling for Feature Selection in SVMs
Dimensionally Tight Bounds for Second-Order Hamiltonian Monte Carlo
Safe Reinforcement Learning with Natural Language Constraints
On the Use of Projection Pursuit Constraints for Training Neural Networks
Adaptive Step-Size for Policy Gradient Methods
Second-Order Neural ODE Optimizer
Serial Order in Reading Aloud: Connectionist Models and Neighborhood Structure
GP CaKe: Effective brain connectivity with causal kernels
Learning from Offline Foundation Features with Tensor Augmentations
Ensemble of Averages: Improving Model Selection and Boosting Performance in Domain Generalization
NeurIPS 2021 Competitions and Demonstrations Track, 6-14 December 2021, Online
Continuous Contrastive Learning for Long-Tailed Semi-Supervised Recognition
Space-Time Continuous PDE Forecasting using Equivariant Neural Fields
Semi-supervised Regression using Hessian energy with an application to semi-supervised dimensionality reduction
Convergence Analysis of Two-layer Neural Networks with ReLU Activation
The discriminant center-surround hypothesis for bottom-up saliency
Designing by Training: Acceleration Neural Network for Fast High-Dimensional Convolution
Understanding Deep Gradient Leakage via Inversion Influence Functions
Truncated Marginal Neural Ratio Estimation
Online Optimal Control with Linear Dynamics and Predictions: Algorithms and Regret Analysis
Post-processing for Individual Fairness
Motion Consistency Model: Accelerating Video Diffusion with Disentangled Motion-Appearance Distillation
Augmenting Online Algorithms with $\varepsilon$-Accurate Predictions
A Simple Remedy for Dataset Bias via Self-Influence: A Mislabeled Sample Perspective
Unified View of Matrix Completion under General Structural Constraints
A Framework for Multiple-Instance Learning
BricksRL: A Platform for Democratizing Robotics and Reinforcement Learning Research and Education with LEGO
The staircase property: How hierarchical structure can guide deep learning
No Subclass Left Behind: Fine-Grained Robustness in Coarse-Grained Classification Problems
Annealed Multiple Choice Learning: Overcoming limitations of Winner-takes-all with annealing
Exploiting Tractable Substructures in Intractable Networks
Compositional Abilities Emerge Multiplicatively: Exploring Diffusion Models on a Synthetic Task
Infinite Limits of Multi-head Transformer Dynamics
Robust Regression via Hard Thresholding
Learning to Make Coherent Predictions in Domains with Discontinuities
Noise-Tolerant Interactive Learning Using Pairwise Comparisons
WildGaussians: 3D Gaussian Splatting In the Wild
Unified Methods for Exploiting Piecewise Linear Structure in Convex Optimization
Hedging as Reward Augmentation in Probabilistic Graphical Models
Parameter Symmetry and Noise Equilibrium of Stochastic Gradient Descent
Help or Hinder: Bayesian Models of Social Goal Inference
Log-normality and Skewness of Estimated State/Action Values in Reinforcement Learning
Neural Architecture Search with Bayesian Optimisation and Optimal Transport
Locality Sensitive Hashing in Fourier Frequency Domain For Soft Set Containment Search
Learning Supervised PageRank with Gradient-Based and Gradient-Free Optimization Methods
Topic-Partitioned Multinetwork Embeddings
Nash Propagation for Loopy Graphical Games
MetaQuant: Learning to Quantize by Learning to Penetrate Non-differentiable Quantization
Acquisition in Autoshaping
Task-Driven Convolutional Recurrent Models of the Visual System
Shape Registration in the Time of Transformers
An Efficient Transfer Learning Framework for Multiagent Reinforcement Learning
Evaluation of Contrastive Predictive Coding for Histopathology Applications
Human-3Diffusion: Realistic Avatar Creation via Explicit 3D Consistent Diffusion Models
Fast, Sample-Efficient Algorithms for Structured Phase Retrieval
Online Relational Inference for Evolving Multi-agent Interacting Systems
Privacy without Noisy Gradients: Slicing Mechanism for Generative Model Training
Node Classification on Graphs with Few-Shot Novel Labels via Meta Transformed Network Embedding
Charting a Manifold
Sparse recovery by thresholded non-negative least squares
Towards Explaining the Regularization Effect of Initial Large Learning Rate in Training Neural Networks
Towards Label Position Bias in Graph Neural Networks
Slot State Space Models
Exploiting weakly-labeled Web images to improve object classification: a domain adaptation approach
Unsupervised Optical Flow Estimation with Dynamic Timing Representation for Spike Camera
Fitting summary statistics of neural data with a differentiable spiking network simulator
Extending Q-Learning to General Adaptive Multi-Agent Systems
Regularization With Stochastic Transformations and Perturbations for Deep Semi-Supervised Learning
VisAlign: Dataset for Measuring the Alignment between AI and Humans in Visual Perception
Network size and size of the weights in memorization with two-layers neural networks
Accelerating ERM for data-driven algorithm design using output-sensitive techniques
On the Optimization Landscape of Tensor Decompositions
Modeling Memory Transfer and Saving in Cerebellar Motor Learning
PreDiff: Precipitation Nowcasting with Latent Diffusion Models
Probabilistic Transformer For Time Series Analysis
(Probably) Concave Graph Matching
Framework and Benchmarks for Combinatorial and Mixed-variable Bayesian Optimization
Submodularity Cuts and Applications
Agree to Disagree: Adaptive Ensemble Knowledge Distillation in Gradient Space
Exchangeable Neural ODE for Set Modeling
Robust PCA with compressed data
Max-Margin Structured Output Regression for Spatio-Temporal Action Localization
Optimal Query Complexity of Secure Stochastic Convex Optimization
QUARK: Controllable Text Generation with Reinforced Unlearning
Global Ranking Using Continuous Conditional Random Fields
Learning under Model Misspecification: Applications to Variational and Ensemble methods
Learning the Dependency Structure of Latent Factors
Learning Energy-based Model via Dual-MCMC Teaching
Regular and Irregular Gallager-zype Error-Correcting Codes
Generative Modeling of Molecular Dynamics Trajectories
Analysis of Krylov Subspace Solutions of Regularized Non-Convex Quadratic Problems
ProlificDreamer: High-Fidelity and Diverse Text-to-3D Generation with Variational Score Distillation
A Non-Asymptotic Analysis for Stein Variational Gradient Descent
Receding Horizon Differential Dynamic Programming
Sharp Spectral Rates for Koopman Operator Learning
Extraction and Recovery of Spatio-Temporal Structure in Latent Dynamics Alignment with Diffusion Model
Towards Diverse and Faithful One-shot Adaption of Generative Adversarial Networks
Modeling the Modulatory Effect of Attention on Human Spatial Vision
Adversarial Robustness of Supervised Sparse Coding
Better Generative Models for Sequential Data Problems: Bidirectional Recurrent Mixture Density Networks
Nonnegative Sparse PCA
Data-driven calibration of linear estimators with minimal penalties
Some Solutions to the Missing Feature Problem in Vision
DermGAN: Synthetic Generation of Clinical Skin Images with Pathology
Investigating Gender Bias in Language Models Using Causal Mediation Analysis
DECRL: A Deep Evolutionary Clustering Jointed Temporal Knowledge Graph Representation Learning Approach
UniXGrad: A Universal, Adaptive Algorithm with Optimal Guarantees for Constrained Optimization
QuadAttacK: A Quadratic Programming Approach to Learning Ordered Top-K Adversarial Attacks
A generalized neural tangent kernel for surrogate gradient learning
Do Wider Neural Networks Really Help Adversarial Robustness?
Divergence-Augmented Policy Optimization
An Autonomous Robotic System for Mapping Abandoned Mines
Distributed Information Regularization on Graphs
Improving Policy-Constrained Kidney Exchange via Pre-Screening
WildVision: Evaluating Vision-Language Models in the Wild with Human Preferences
An Oracle Inequality for Clipped Regularized Risk Minimizers
DFacTo: Distributed Factorization of Tensors
Dynamic Sasvi: Strong Safe Screening for Norm-Regularized Least Squares
Beyond Deep Ensembles: A Large-Scale Evaluation of Bayesian Deep Learning under Distribution Shift
Worst-Case Offline Reinforcement Learning with Arbitrary Data Support
Bayesian Image Super-Resolution
Improved Guarantees for Fully Dynamic k-Center Clustering with Outliers in General Metric Spaces
Decomposable Non-Smooth Convex Optimization with Nearly-Linear Gradient Oracle Complexity
Designing Linear Threshold Based Neural Network Pattern Classifiers
Computing Motion Using Resistive Networks
Post-Training Sparsity-Aware Quantization
Effectiveness of Vision Transformer for Fast and Accurate Single-Stage Pedestrian Detection
Greedy Importance Sampling
On the Value of Infinite Gradients in Variational Autoencoder Models
Meta-Learning via Learning with Distributed Memory
Multiclass Learning from Contradictions
Learning User Perceived Clusters with Feature-Level Supervision
Efficient Algorithms for Generalized Linear Bandits with Heavy-tailed Rewards
The Landscape of Non-convex Empirical Risk with Degenerate Population Risk
ParallelEdits: Efficient Multi-Aspect Text-Driven Image Editing with Attention Grouping
On the Use of Anchoring for Training Vision Models
Grammar-Based Grounded Lexicon Learning
Recurrent Reinforcement Learning with Memoroids
Unreasonable Effectiveness of Greedy Algorithms in Multi-Armed Bandit with Many Arms
Completely random measures for modelling block-structured sparse networks
Unifying lower bounds on prediction dimension of convex surrogates
Conformal Prediction with Temporal Quantile Adjustments
Learning the Efficient Frontier
The Fragility of Fairness: Causal Sensitivity Analysis for Fair Machine Learning
Reinforcement Learning in Robust Markov Decision Processes
Towards Robust Interpretability with Self-Explaining Neural Networks
Dual T: Reducing Estimation Error for Transition Matrix in Label-noise Learning
Variance Reduction in Stochastic Gradient Langevin Dynamics
Multi-Object Representation Learning via Feature Connectivity and Object-Centric Regularization
The Benefits of Being Distributional: Small-Loss Bounds for Reinforcement Learning
Learning Physical Dynamics with Subequivariant Graph Neural Networks
Convolutional Visual Prompt for Robust Visual Perception
Collaborative Gaussian Processes for Preference Learning
E-MAPP: Efficient Multi-Agent Reinforcement Learning with Parallel Program Guidance
Multiple Kernel Learning and the SMO Algorithm
Invariance Learning based on Label Hierarchy
Extended Regularization Methods for Nonconvergent Model Selection
Unlabeled data: Now it helps, now it doesn't
Similarity-Navigated Conformal Prediction for Graph Neural Networks
Symbol-LLM: Leverage Language Models for Symbolic System in Visual Human Activity Reasoning
Cross-Scale Internal Graph Neural Network for Image Super-Resolution
Auto-Panoptic: Cooperative Multi-Component Architecture Search for Panoptic Segmentation
Provably adaptive reinforcement learning in metric spaces
How does GPT-2 compute greater-than?: Interpreting mathematical abilities in a pre-trained language model
A Performance-Driven Benchmark for Feature Selection in Tabular Deep Learning
From Trojan Horses to Castle Walls: Unveiling Bilateral Data Poisoning Effects in Diffusion Models
Doubly Constrained Fair Clustering
Scaled Least Squares Estimator for GLMs in Large-Scale Problems
Embedding Logical Queries on Knowledge Graphs
VisionLLM v2: An End-to-End Generalist Multimodal Large Language Model for Hundreds of Vision-Language Tasks
On Measuring Fairness in Generative Models
Better Best of Both Worlds Bounds for Bandits with Switching Costs
Consistent Sufficient Explanations and Minimal Local Rules for explaining the decision of any classifier or regressor
Annealing and the Rate Distortion Problem
Robust Multi-Class Gaussian Process Classification
Prior-independent Dynamic Auctions for a Value-maximizing Buyer
Bridging the Gap between Object and Image-level Representations for Open-Vocabulary Detection
Statistics of Natural Images: Scaling in the Woods
The Kernel Beta Process
MAP Propagation Algorithm: Faster Learning with a Team of Reinforcement Learning Agents
Adaptation in Speech Motor Control
Recovering Simultaneously Structured Data via Non-Convex Iteratively Reweighted Least Squares
Unbounded Differentially Private Quantile and Maximum Estimation
Function Approximation with the Sweeping Hinge Algorithm
Quilt-1M: One Million Image-Text Pairs for Histopathology
Computing with Arrays of Bell-Shaped and Sigmoid Functions
Efficient Algorithms for Non-convex Isotonic Regression through Submodular Optimization
Information Directed Sampling for Sparse Linear Bandits
Dynamic Clustering via Asymptotics of the Dependent Dirichlet Process Mixture
Learning Efficient Auditory Codes Using Spikes Predicts Cochlear Filters
SceneScape: Text-Driven Consistent Scene Generation
The Challenges of the Nonlinear Regime for Physics-Informed Neural Networks
Instability and Local Minima in GAN Training with Kernel Discriminators
PAC-Bayesian Bound for the Conditional Value at Risk
A Screening Rule for l1-Regularized Ising Model Estimation
Echoes Beyond Points: Unleashing the Power of Raw Radar Data in Multi-modality Fusion
Expressive probabilistic sampling in recurrent neural networks
Citcuits for VLSI Implementation of Temporally Asymmetric Hebbian Learning
Blind Image Restoration via Fast Diffusion Inversion
Semi-flat minima and saddle points by embedding neural networks to overparameterization
Coresets for Time Series Clustering
Extensible Prompts for Language Models on Zero-shot Language Style Customization
What Does the Hippocampus Compute?: A Precis of the 1993 NIPS Workshop
Generalized Block-Diagonal Structure Pursuit: Learning Soft Latent Task Assignment against Negative Transfer
Correlated Uncertainty for Learning Dense Correspondences from Noisy Labels
Concept Algebra for (Score-Based) Text-Controlled Generative Models
A Nonconvex Optimization Framework for Low Rank Matrix Estimation
Learning on Random Balls is Sufficient for Estimating (Some) Graph Parameters
Active clustering for labeling training data
Frequency Domain-Based Dataset Distillation
Learning in large linear perceptrons and why the thermodynamic limit is relevant to the real world
Mixed Optimization for Smooth Functions
The Sound of APALM Clapping: Faster Nonsmooth Nonconvex Optimization with Stochastic Asynchronous PALM
ActionAtlas: A VideoQA Benchmark for Domain-specialized Action Recognition
A Graph Theoretic Additive Approximation of Optimal Transport
Probabilistic Interpretation of Population Codes
SegFormer: Simple and Efficient Design for Semantic Segmentation with Transformers
Regret Minimization in MDPs with Options without Prior Knowledge
Query by Committee Made Real
Globally Convergent Variational Inference
Automatic Construction of Evaluation Suites for Natural Language Generation Datasets
A Theory of the Distortion-Perception Tradeoff in Wasserstein Space
Benchmarking the Combinatorial Generalizability of Complex Query Answering on Knowledge Graphs
Unsupervised Semantic Aggregation and Deformable Template Matching for Semi-Supervised Learning
Learning About Objects by Learning to Interact with Them
Simultaneous Missing Value Imputation and Structure Learning with Groups
Generalization Bounds for Estimating Causal Effects of Continuous Treatments
Integrated Non-Factorized Variational Inference
Gradient Informed Proximal Policy Optimization
Is Sortition Both Representative and Fair?
Non-Gaussian Tensor Programs
An Image is Worth More Than a Thousand Words: Towards Disentanglement in The Wild
Importance-aware Co-teaching for Offline Model-based Optimization
Synchrony and Desynchrony in Neural Oscillator Networks
Partial Structure Discovery is Sufficient for No-regret Learning in Causal Bandits
Continual Learning of a Mixed Sequence of Similar and Dissimilar Tasks
End-to-end Learnable Clustering for Intent Learning in Recommendation
Looking Outside the Searchlight
Controllable Unsupervised Text Attribute Transfer via Editing Entangled Latent Representation
Sketching based Representations for Robust Image Classification with Provable Guarantees
Reciprocal Adversarial Learning via Characteristic Functions
Analyzing Cross-Connected Networks
A Benchmark Dataset for Event-Guided Human Pose Estimation and Tracking in Extreme Conditions
Organizing recurrent network dynamics by task-computation to enable continual learning
Understanding Probabilistic Sparse Gaussian Process Approximations
Fast Algorithms for Packing Proportional Fairness and its Dual
Model Sensitivity Aware Continual Learning
Sparseness of Support Vector Machines---Some Asymptotically Sharp Bounds
An Efficient End-to-End Training Approach for Zero-Shot Human-AI Coordination
Partial Identification of Treatment Effects with Implicit Generative Models
The Cluster Description Problem - Complexity Results, Formulations and Approximations
Future-Dependent Value-Based Off-Policy Evaluation in POMDPs
Robust Persistence Diagrams using Reproducing Kernels
Direction Selective Silicon Retina that Uses Null Inhibition
Neglected Hessian component explains mysteries in sharpness regularization
Kernel Language Entropy: Fine-grained Uncertainty Quantification for LLMs from Semantic Similarities
A Biologically Plausible Model for Rapid Natural Scene Identification
BR-SNIS: Bias Reduced Self-Normalized Importance Sampling
Self-Consistent Velocity Matching of Probability Flows
Sparse Convolved Gaussian Processes for Multi-output Regression
A Spike Based Learning Neuron in Analog VLSI
Reliable Decision Support using Counterfactual Models
Improving Compositionality of Neural Networks by Decoding Representations to Inputs
Large-Scale Learning with Fourier Features and Tensor Decompositions
The Dormant Neuron Phenomenon in Multi-Agent Reinforcement Learning Value Factorization
DiffGS: Functional Gaussian Splatting Diffusion
An ideal observer model of infant object perception
Learning concept graphs from text with stick-breaking priors
Infra-slow brain dynamics as a marker for cognitive function and decline
Log-concave Sampling from a Convex Body with a Barrier: a Robust and Unified Dikin Walk
String Kernels, Fisher Kernels and Finite State Automata
Grammar as a Foreign Language
A Dynamical Systems Approach for a Learnable Autonomous Robot
Uncovering the Hidden Dynamics of Video Self-supervised Learning under Distribution Shifts
The Epoch-Greedy Algorithm for Multi-armed Bandits with Side Information
Adaptive Visual Scene Understanding: Incremental Scene Graph Generation
MetaPoison: Practical General-purpose Clean-label Data Poisoning
FloatBoost Learning for Classification
An Application of the Principle of Maximum Information Preservation to Linear Systems
Particle Cloud Generation with Message Passing Generative Adversarial Networks
Latent Gaussian Activity Propagation: Using Smoothness and Structure to Separate and Localize Sounds in Large Noisy Environments
Spectroscopic Detection of Cervical Pre-Cancer through Radial Basis Function Networks
Adaptive knot Placement for Nonparametric Regression
Marginal Utility for Planning in Continuous or Large Discrete Action Spaces
Composing Parameter-Efficient Modules with Arithmetic Operation
Qu-ANTI-zation: Exploiting Quantization Artifacts for Achieving Adversarial Outcomes
Model Collapse Demystified: The Case of Regression
SUBP: Soft Uniform Block Pruning for 1×N Sparse CNNs Multithreading Acceleration
The Representation Landscape of Few-Shot Learning and Fine-Tuning in Large Language Models
Learning Composable Energy Surrogates for PDE Order Reduction
Boosting Out-of-distribution Detection with Typical Features
Iterative ranking from pair-wise comparisons
AnyFit: Controllable Virtual Try-on for Any Combination of Attire Across Any Scenario
Learning elementary structures for 3D shape generation and matching
VisionLLM: Large Language Model is also an Open-Ended Decoder for Vision-Centric Tasks
Efficient Direct Density Ratio Estimation for Non-stationarity Adaptation and Outlier Detection
Deliberation Networks: Sequence Generation Beyond One-Pass Decoding
Federated Natural Policy Gradient and Actor Critic Methods for Multi-task Reinforcement Learning
Learning diverse causally emergent representations from time series data
CALE: Continuous Arcade Learning Environment
Minibatch vs Local SGD for Heterogeneous Distributed Learning
Decision-based Black-box Attack Against Vision Transformers via Patch-wise Adversarial Removal
Safety through feedback in Constrained RL
VigDet: Knowledge Informed Neural Temporal Point Process for Coordination Detection on Social Media
ISTA-NAS: Efficient and Consistent Neural Architecture Search by Sparse Coding
Dynamic Pruning of Factor Graphs for Maximum Marginal Prediction
Rotting Bandits
Selective Attention: Enhancing Transformer through Principled Context Control
Learning Generative Models with the Up-Propagation Algorithm
Learning a Single Neuron Robustly to Distributional Shifts and Adversarial Label Noise
Learning Syntactic Patterns for Automatic Hypernym Discovery
A Simple yet Universal Framework for Depth Completion
Learning from Highly Sparse Spatio-temporal Data
Cue Integration for Figure/Ground Labeling