yusuke1997/dblp-id-title huggingface dataset:
Making Offline RL Online: Collaborative World Models for Offline Visual Reinforcement Learning
Kaleidoscope: Learnable Masks for Heterogeneous Multi-agent Reinforcement Learning
SE(3) Diffusion Model-based Point Cloud Registration for Robust 6D Object Pose Estimation
The State of Data Curation at NeurIPS: An Assessment of Dataset Development Practices in the Datasets and Benchmarks Track
Label-Imbalanced and Group-Sensitive Classification under Overparameterization
Interpreting and Analysing CLIP's Zero-Shot Image Classification via Mutual Knowledge
Deconvolutional Paragraph Representation Learning
Using Large Ensembles of Control Variates for Variational Inference
Identifying signal and noise structure in neural population activity with Gaussian process factor models
Robust Imitation via Mirror Descent Inverse Reinforcement Learning
SustainGym: Reinforcement Learning Environments for Sustainable Energy Systems
Online Budgeted Matching with General Bids
Learning Temporal Pose Estimation from Sparsely-Labeled Videos
In-Context Symmetries: Self-Supervised Learning through Contextual World Models
Meiosis Networks
Learning and using relational theories
Implicit Semantic Response Alignment for Partial Domain Adaptation
Auction Mechanism Design for Multi-Robot Coordination
DiPEx: Dispersing Prompt Expansion for Class-Agnostic Object Detection
Speculative Decoding with CTC-based Draft Model for LLM Inference Acceleration
Towards Stable Representations for Protein Interface Prediction
Automated Refinement of Bayes Networks' Parameters based on Test Ordering Constraints
Efficient Adversarial Training without Attacking: Worst-Case-Aware Robust Reinforcement Learning
Fundamental Convergence Analysis of Sharpness-Aware Minimization
SEEMORE: A View-Based Approach to 3-D Object Recognition Using Multiple Visual Cues
When to Act and When to Ask: Policy Learning With Deferral Under Hidden Confounding
The Adaptive Doubly Robust Estimator and a Paradox Concerning Logging Policy
Neural Dubber: Dubbing for Videos According to Scripts
LBD: Decouple Relevance and Observation for Individual-Level Unbiased Learning to Rank
Automatic Outlier Rectification via Optimal Transport
Efficient Multi-task Reinforcement Learning with Cross-Task Policy Guidance
What Ails One-Shot Image Segmentation: A Data Perspective
Gradient-Free Kernel Stein Discrepancy
Revisiting, Benchmarking and Understanding Unsupervised Graph Domain Adaptation
Toward Conditional Distribution Calibration in Survival Prediction
Bayesian time series classification
Pairwise Causality Guided Transformers for Event Sequences
Time-Varying LoRA: Towards Effective Cross-Domain Fine-Tuning of Diffusion Models
Optimal Neural Codes for Control and Estimation
Exponential Family Model-Based Reinforcement Learning via Score Matching
VQ-GNN: A Universal Framework to Scale up Graph Neural Networks using Vector Quantization
No-Press Diplomacy: Modeling Multi-Agent Gameplay
An Analog VLSI Splining Network
Differentiable Neural Architecture Search in Equivalent Space with Exploration Enhancement
Robustifying Generalizable Implicit Shape Networks with a Tunable Non-Parametric Model
DM2C: Deep Mixed-Modal Clustering
Phase transitions for high-dimensional joint support recovery
Network Activity Determines Spatio-Temporal Integration in Single Cells
Time-Reversed Dissipation Induces Duality Between Minimizing Gradient Norm and Function Value
SpokenWOZ: A Large-Scale Speech-Text Benchmark for Spoken Task-Oriented Dialogue Agents
General Control Functions for Causal Effect Estimation from IVs
Linear Feature Encoding for Reinforcement Learning
Domain Adaptation as a Problem of Inference on Graphical Models
Fast Krylov Methods for N-Body Learning
Exploiting a Zoo of Checkpoints for Unseen Tasks
PyNeRF: Pyramidal Neural Radiance Fields
Direction Selectivity In Primary Visual Cortex Using Massive Intracortical Connections
Quantitative Convergences of Lie Group Momentum Optimizers
Differentiable Learning Under Triage
KFC: A Scalable Approximation Algorithm for $k$-center Fair Clustering
Statistical Models of Linear and Nonlinear Contextual Interactions in Early Visual Processing
How Perception Guides Production in Birdsong Learning
Bridging Central and Local Differential Privacy in Data Acquisition Mechanisms
Gradient descent GAN optimization is locally stable
Counterexample Guided RL Policy Refinement Using Bayesian Optimization
Deep Neural Nets with Interpolating Function as Output Activation
Probabilistic Linear Solvers for Machine Learning
Automated Dynamic Mechanism Design
$k$-Sliced Mutual Information: A Quantitative Study of Scalability with Dimension
A Mathematical Framework for Quantifying Transferability in Multi-source Transfer Learning
An information-theoretic quantification of the content of communication between brain regions
Object-Based Analog VLSI Vision Circuits
Improving Environment Novelty Quantification for Effective Unsupervised Environment Design
Information Theoretic Counterfactual Learning from Missing-Not-At-Random Feedback
Why do tree-based models still outperform deep learning on typical tabular data?
Improved Algorithms for Linear Stochastic Bandits
Linearly constrained Bayesian matrix factorization for blind source separation
Iteratively Reweighted Least Squares for Basis Pursuit with Global Linear Convergence Rate
A Universal Analysis of Large-Scale Regularized Least Squares Solutions
Sample-Efficient Geometry Reconstruction from Euclidean Distances using Non-Convex Optimization
Complexity Issues in Neural Computation and Learning
Evaluating model performance under worst-case subpopulations
An Architectural Mechanism for Direction-tuned Cortical Simple Cells: The Role of Mutual Inhibition
CrossGNN: Confronting Noisy Multivariate Time Series Via Cross Interaction Refinement
Symmetric Correspondence Topic Models for Multilingual Text Analysis
Spherical convolutions and their application in molecular modelling
Learning Disentangled Behavior Embeddings
SeeClear: Semantic Distillation Enhances Pixel Condensation for Video Super-Resolution
Algorithmic Regularization in Learning Deep Homogeneous Models: Layers are Automatically Balanced
Self-Refining Diffusion Samplers: Enabling Parallelization via Parareal Iterations
Message passing for task redistribution on sparse graphs
When Does Confidence-Based Cascade Deferral Suffice?
Verification and search algorithms for causal DAGs
A Primal-Dual Message-Passing Algorithm for Approximated Large Scale Structured Prediction
Disentangling Influence: Using disentangled representations to audit model predictions
4DBInfer: A 4D Benchmarking Toolbox for Graph-Centric Predictive Modeling on RDBs
Simple and Scalable Sparse k-means Clustering via Feature Ranking
On Plasticity, Invariance, and Mutually Frozen Weights in Sequential Task Learning
Convex and Non-convex Optimization Under Generalized Smoothness
StyleDrop: Text-to-Image Synthesis of Any Style
Robustness Analysis of Video-Language Models Against Visual and Language Perturbations
What I Cannot Predict, I Do Not Understand: A Human-Centered Evaluation Framework for Explainability Methods
Multi-Scale VMamba: Hierarchy in Hierarchy Visual State Space Model
Global Optimal K-Medoids Clustering of One Million Samples
Foundations for a Circuit Complexity Theory of Sensory Processing
Unsupervised Discovery of Formulas for Mathematical Constants
Deep Model Reassembly
Fast Graph Sharpness-Aware Minimization for Enhancing and Accelerating Few-Shot Node Classification
Direct Estimation of Differential Functional Graphical Models
The Primal-Dual method for Learning Augmented Algorithms
A Unified Model for Multi-class Anomaly Detection
LIPS - Learning Industrial Physical Simulation benchmark suite
Communication-Efficient Federated Bilevel Optimization with Global and Local Lower Level Problems
GS-Blur: A 3D Scene-Based Dataset for Realistic Image Deblurring
Tensor Monte Carlo: Particle Methods for the GPU era
Coresets for Robust Training of Deep Neural Networks against Noisy Labels
Quantizable Transformers: Removing Outliers by Helping Attention Heads Do Nothing
Modeling Human Motion Using Binary Latent Variables
Structured Local Minima in Sparse Blind Deconvolution
STREETS: A Novel Camera Network Dataset for Traffic Flow
BanditPAM++: Faster k-medoids Clustering
CaptainCook4D: A Dataset for Understanding Errors in Procedural Activities
MSDS: A Large-Scale Chinese Signature and Token Digit String Dataset for Handwriting Verification
To Learn or Not to Learn, That is the Question - A Feature-Task Dual Learning Model of Perceptual Learning
Learning from Inside: Self-driven Siamese Sampling and Reasoning for Video Question Answering
An Empirical Study of Graph Contrastive Learning
Understanding Deflation Process in Over-parametrized Tensor Decomposition
Integrating Tree Path in Transformer for Code Representation
Gaussianization
DeSparsify: Adversarial Attack Against Token Sparsification Mechanisms
JourneyDB: A Benchmark for Generative Image Understanding
Universal Approximnation and Learning of Trajectories Using Oscillators
Uncovering Safety Risks of Large Language Models through Concept Activation Vector
Denoised Smoothing: A Provable Defense for Pretrained Classifiers
Tree Variational Autoencoders
Knowledge Distillation: Bad Models Can Be Good Role Models
Approximate Policy Iteration with a Policy Language Bias
Markov Chain Score Ascent: A Unifying Framework of Variational Inference with Markovian Gradients
CapProNet: Deep Feature Learning via Orthogonal Projections onto Capsule Subspaces
Rethinking the compositionality of point clouds through regularization in the hyperbolic space
Feedback Synapse to Cone and Light Adaptation
Unsupervised Image Denoising with Score Function
DeepSimHO: Stable Pose Estimation for Hand-Object Interaction via Physics Simulation
What Are the Invariant Occlusive Components of Image Patches? A Probabilistic Generative Approach
Blurred-Dilated Method for Adversarial Attacks
Multi-Task Temporal Shift Attention Networks for On-Device Contactless Vitals Measurement
Sequoia: Scalable and Robust Speculative Decoding
TotalSelfScan: Learning Full-body Avatars from Self-Portrait Videos of Faces, Hands, and Bodies
A Gaussian Process-Bayesian Bernoulli Mixture Model for Multi-Label Active Learning
Self-Supervised Fair Representation Learning without Demographics
VisFIS: Visual Feature Importance Supervision with Right-for-the-Right-Reason Objectives
Robustness Verification of Tree-based Models
Masked Prediction: A Parameter Identifiability View
Binary Radiance Fields
The Bayesian Case Model: A Generative Approach for Case-Based Reasoning and Prototype Classification
Boosting Barely Robust Learners: A New Perspective on Adversarial Robustness
Confidence-based Reliable Learning under Dual Noises
Pairwise Analysis for Longitudinal fMRI Studies
Harmony4D: A Video Dataset for In-The-Wild Close Human Interactions
CODA: Generalizing to Open and Unseen Domains with Compaction and Disambiguation
Robust Regression and Lasso
Online Training Through Time for Spiking Neural Networks
Maximum Common Subgraph Guided Graph Retrieval: Late and Early Interaction Networks
Part-based Probabilistic Point Matching using Equivalence Constraints
MaxGap Bandit: Adaptive Algorithms for Approximate Ranking
Generalization Error Rates in Kernel Regression: The Crossover from the Noiseless to Noisy Regime
Deep Clustered Convolutional Kernels
DTWNet: a Dynamic Time Warping Network
Generalized Independent Noise Condition for Estimating Latent Variable Causal Graphs
Autoregressive Perturbations for Data Poisoning
Optimizing Information-theoretical Generalization Bound via Anisotropic Noise of SGLD
A Framework for the Cooperation of Learning Algorithms
A new dataset for multilingual keyphrase generation
Benchmarking Uncertainty Disentanglement: Specialized Uncertainties for Specialized Tasks
$\texttt{LeadCache}$: Regret-Optimal Caching in Networks
Invertible Tabular GANs: Killing Two Birds with One Stone for Tabular Data Synthesis
Unsupervised Learning of Compositional Energy Concepts
Calibration by Distribution Matching: Trainable Kernel Calibration Metrics
Divide-and-Conquer Learning by Anchoring a Conical Hull
Collaborative Learning in the Jungle (Decentralized, Byzantine, Heterogeneous, Asynchronous and Nonconvex Learning)
Practical Characteristics of Neural Network and Conventional Patterns Classifiers
Encoding High Dimensional Local Features by Sparse Coding Based Fisher Vectors
Bridging Offline Reinforcement Learning and Imitation Learning: A Tale of Pessimism
Connectionist Approaches to the Use of Markov Models for Speech Recognition
Fine-Tuning Personalization in Federated Learning to Mitigate Adversarial Clients
Causal Confusion in Imitation Learning
Adaptive Smoothed Online Multi-Task Learning
MCMC for Variationally Sparse Gaussian Processes
Learning-Augmented Algorithms for Online Linear and Semidefinite Programming
On the Periodic Behavior of Neural Network Training with Batch Normalization and Weight Decay
Tight First- and Second-Order Regret Bounds for Adversarial Linear Bandits
Meta-Adaptive Nonlinear Control: Theory and Algorithms
CO-Optimal Transport
On the Use of Non-Stationary Policies for Stationary Infinite-Horizon Markov Decision Processes
New Outer Bounds on the Marginal Polytope
Minimum description length (MDL) regularization for online learning
Dual Lagrangian Learning for Conic Optimization
Open-Ended Reinforcement Learning with Neural Reward Functions
Coresets for Vertical Federated Learning: Regularized Linear Regression and $K$-Means Clustering
Constrained Update Projection Approach to Safe Policy Optimization
On $f$-Divergence Principled Domain Adaptation: An Improved Framework
DDCoT: Duty-Distinct Chain-of-Thought Prompting for Multimodal Reasoning in Language Models
3DGS-Enhancer: Enhancing Unbounded 3D Gaussian Splatting with View-consistent 2D Diffusion Priors
OSWorld: Benchmarking Multimodal Agents for Open-Ended Tasks in Real Computer Environments
DECAF: Generating Fair Synthetic Data Using Causally-Aware Generative Networks
Hypothesis Testing for Differentially Private Linear Regression
Imitation-Projected Programmatic Reinforcement Learning
Optimization of Smooth Functions with Noisy Observations: Local Minimax Rates
(Optimal) Online Bipartite Matching with Degree Information
A Computationally Efficient Sparsified Online Newton Method
Few-Shot Non-Parametric Learning with Deep Latent Variable Model
Learning by Doing: Controlling a Dynamical System using Causality, Control, and Reinforcement Learning
Meta-Auto-Decoder for Solving Parametric Partial Differential Equations
Compositional Policy Learning in Stochastic Control Systems with Formal Guarantees
Robust Kernel Principal Component Analysis
ERBench: An Entity-Relationship based Automatically Verifiable Hallucination Benchmark for Large Language Models
The Use of MDL to Select among Computational Models of Cognition
Using Surrogates in Covariate-adjusted Response-adaptive Randomization Experiments with Delayed Outcomes
Safe and Efficient Off-Policy Reinforcement Learning
Scalable Robust Matrix Factorization with Nonconvex Loss
Bayesian Reconstruction of 3D Human Motion from Single-Camera Video
Better Set Representations For Relational Reasoning
Learning with Differentiable Pertubed Optimizers
A Neural Compositional Paradigm for Image Captioning
Detecting and Adapting to Irregular Distribution Shifts in Bayesian Online Learning
Rate- and Phase-coded Autoassociative Memory
Reinforcement Learning by Probability Matching
Information Rates and Optimal Decoding in Large Neural Populations
Meta-Learning Universal Priors Using Non-Injective Change of Variables
Domain Re-Modulation for Few-Shot Generative Domain Adaptation
Local Linear Convergence of Forward-Backward under Partial Smoothness
Thompson Sampling for 1-Dimensional Exponential Family Bandits
Hybrid Macro/Micro Level Backpropagation for Training Deep Spiking Neural Networks
Latent distance estimation for random geometric graphs
Predictive Sequence Learning in Recurrent Neocortical Circuits
ALVINN: An Autonomous Land Vehicle in a Neural Network
CHIP: CHannel Independence-based Pruning for Compact Neural Networks
L_DMI: A Novel Information-theoretic Loss Function for Training Deep Nets Robust to Label Noise
The Connectivity Analysis of Simple Association
Text-Based Information Retrieval Using Exponentiated Gradient Descent
COPT: Coordinated Optimal Transport on Graphs
DaDA: Distortion-aware Domain Adaptation for Unsupervised Semantic Segmentation
Experimental Demonstrations of Optical Neural Computers
Non-monotone Continuous DR-submodular Maximization: Structure and Algorithms
Faster Accelerated First-order Methods for Convex Optimization with Strongly Convex Function Constraints
Text2NKG: Fine-Grained N-ary Relation Extraction for N-ary relational Knowledge Graph Construction
Learning Partial Equivariances From Data
Nonparametric regression and classification with joint sparsity constraints
Multi-source Domain Adaptation for Semantic Segmentation
OccamLLM: Fast and Exact Language Model Arithmetic in a Single Step
Genetic-Gated Networks for Deep Reinforcement Learning
Training Knowledge-Based Neural Networks to Recognize Genes
Explaining human multiple object tracking as resource-constrained approximate inference in a dynamic probabilistic model
Combinatorial Cascading Bandits
A flexible model for training action localization with varying levels of supervision
Model Matching and SFMD Computation
Spectral Adapter: Fine-Tuning in Spectral Space
The Importance of Being Scalable: Improving the Speed and Accuracy of Neural Network Interatomic Potentials Across Chemical Domains
Reinforcement Learning in Newcomblike Environments
Constrained Differential Optimization
Parameters as interacting particles: long time convergence and asymptotic error scaling of neural networks
Accelerated Gradient Methods for Stochastic Optimization and Online Learning
Deterministic Approximation for Submodular Maximization over a Matroid in Nearly Linear Time
3DET-Mamba: Causal Sequence Modelling for End-to-End 3D Object Detection
Scalable Multi-Agent Reinforcement Learning for Networked Systems with Average Reward
Better Approximation and Faster Algorithm Using the Proximal Average
Stabilized Neural Differential Equations for Learning Dynamics with Explicit Constraints
HYSYNTH: Context-Free LLM Approximation for Guiding Program Synthesis
Private Geometric Median
SureMap: Simultaneous mean estimation for single-task and multi-task disaggregated evaluation
Fast Second Order Stochastic Backpropagation for Variational Inference
Multi-agent active perception with prediction rewards
Efficient inference in matrix-variate Gaussian models with \iid observation noise
Learning Exact Patterns of Quasi-synchronization among Spiking Neurons from Data on Multi-unit Recordings
Slicing Vision Transformer for Flexible Inference
Size and depth of monotone neural networks: interpolation and approximation
Multi-Objective Intrinsic Reward Learning for Conversational Recommender Systems
Invariant and Transportable Representations for Anti-Causal Domain Shifts
Communication Complexity of Distributed Convex Learning and Optimization
A Simple and Practical Algorithm for Differentially Private Data Release
Accelerating Reinforcement Learning through GPU Atari Emulation
Multi-Prediction Deep Boltzmann Machines
CoMix: A Comprehensive Benchmark for Multi-Task Comic Understanding
Markov Networks for Detecting Overalpping Elements in Sequence Data
Learning Minimum Volume Sets
Sequence Modeling with Unconstrained Generation Order
Bayesian Surprise Attracts Human Attention
Robust Auction Design in the Auto-bidding World
Statistical Models of Conditioning
Spike-based Neuromorphic Model for Sound Source Localization
Identifying Mislabeled Data using the Area Under the Margin Ranking
Granger Components Analysis: Unsupervised learning of latent temporal dependencies
Integrating Markov processes with structural causal modeling enables counterfactual inference in complex systems
Coresets for k-Segmentation of Streaming Data
Blocked Collaborative Bandits: Online Collaborative Filtering with Per-Item Budget Constraints
Flex-MoE: Modeling Arbitrary Modality Combination via the Flexible Mixture-of-Experts
Learning Sparse Metrics, One Feature at a Time
Online Bounds for Bayesian Algorithms
Quantum Bayesian Optimization
Optimistic Regret Minimization for Extensive-Form Games via Dilated Distance-Generating Functions
Is Mamba Compatible with Trajectory Optimization in Offline Reinforcement Learning?
Multiple Physics Pretraining for Spatiotemporal Surrogate Models
Recovering Communities in the General Stochastic Block Model Without Knowing the Parameters
Debiasing Conditional Stochastic Optimization
On the Convexity of Latent Social Network Inference
Automatic Choice of Dimensionality for PCA
A Framework to Learn with Interpretation
Efficient Parallel Learning Algorithms for Neural Networks
Sobolev Acceleration and Statistical Optimality for Learning Elliptic Equations via Gradient Descent
Beyond temperature scaling: Obtaining well-calibrated multi-class probabilities with Dirichlet calibration
Disentangled Representation Learning in Non-Markovian Causal Systems
Learning Monotonic Transformations for Classification
Parameter-free Clipped Gradient Descent Meets Polyak
Automatic and Harmless Regularization with Constrained and Lexicographic Optimization: A Dynamic Barrier Approach
Low-rank Optimal Transport: Approximation, Statistics and Debiasing
Learning the Latent Causal Structure for Modeling Label Noise
Training-Free Adaptive Diffusion with Bounded Difference Approximation Strategy
SNIPS: Solving Noisy Inverse Problems Stochastically
Robustness Analysis of Non-Convex Stochastic Gradient Descent using Biased Expectations
Short-Term Depression in VLSI Stochastic Synapse
Model Agnostic Multilevel Explanations
Derivative Observations in Gaussian Process Models of Dynamic Systems
Filtering Abstract Senses From Image Search Results
Is Q-Learning Provably Efficient?
Amortized Eigendecomposition for Neural Networks
Neural Models for Part-Whole Hierarchies
Rethinking pooling in graph neural networks
Deciding What to Model: Value-Equivalent Sampling for Reinforcement Learning
A multi-agent control framework for co-adaptation in brain-computer interfaces
A Prior of a Googol Gaussians: a Tensor Ring Induced Prior for Generative Models
FinRL-Meta: Market Environments and Benchmarks for Data-Driven Financial Reinforcement Learning
BLoB: Bayesian Low-Rank Adaptation by Backpropagation for Large Language Models
Noisy Dual Mirror Descent: A Near Optimal Algorithm for Jointly-DP Convex Resource Allocation
Implicit Warping for Animation with Image Sets
Focal Modulation Networks
Stable Dual Dynamic Programming
Sharper Generalization Bounds for Pairwise Learning
Inducing brain-relevant bias in natural language processing models
k-Prototype Learning for 3D Rigid Structures
Graph Convolutions Enrich the Self-Attention in Transformers!
ViSioNS: Visual Search in Natural Scenes Benchmark
VLKEB: A Large Vision-Language Model Knowledge Editing Benchmark
CCD Neural Network Processors for Pattern Recognition
Grouping with Bias
Global Convergence of Online Optimization for Nonlinear Model Predictive Control
Online Convex Optimization with Unbounded Memory
Controllable Text Generation with Neurally-Decomposed Oracle
Stochastic Nonparametric Event-Tensor Decomposition
Eye-gaze Guided Multi-modal Alignment for Medical Representation Learning
Adaptive Skills Adaptive Partitions (ASAP)
Threshold Bandits, With and Without Censored Feedback
From Causal to Concept-Based Representation Learning
Learning invariant features using the Transformed Indian Buffet Process
Robust exploration in linear quadratic reinforcement learning
Quantum Algorithms for Sampling Log-Concave Distributions and Estimating Normalizing Constants
Branching Law for Axons
K-Medoids For K-Means Seeding
SEENN: Towards Temporal Spiking Early Exit Neural Networks
Predicting the Politics of an Image Using Webly Supervised Data
Diffusion Model is an Effective Planner and Data Synthesizer for Multi-Task Reinforcement Learning
Training Normalizing Flows with the Information Bottleneck for Competitive Generative Classification
Normalization-Equivariant Neural Networks with Application to Image Denoising