yusuke1997/dblp-id-title huggingface dataset:
Exploring the Edges of Latent State Clusters for Goal-Conditioned Reinforcement Learning
Tackling the Objective Inconsistency Problem in Heterogeneous Federated Optimization
Neural Shape Deformation Priors
Cross-Care: Assessing the Healthcare Implications of Pre-training Data on Language Model Bias
H2O: Heavy-Hitter Oracle for Efficient Generative Inference of Large Language Models
Consistent Classification, Firm and Soft
Revisiting Few-Shot Object Detection with Vision-Language Models
Reconstruct & Crush Network
Hierarchical Neural Architecture Search for Deep Stereo Matching
Transformers learn through gradual rank increase
One-Pass Boosting
Variable KD-Tree Algorithms for Spatial Pattern Search and Discovery
Diverse and Accurate Image Description Using a Variational Auto-Encoder with an Additive Gaussian Encoding Space
A Robust Exact Algorithm for the Euclidean Bipartite Matching Problem
A Theoretical Framework for Inference Learning
Infinite Latent SVM for Classification and Multi-task Learning
Rational Beliefs Real Agents Can Have - A Logical Point of View
Bayesian Clustering of Neural Spiking Activity Using a Mixture of Dynamic Poisson Factor Analyzers
Searching for Character Models
Re-Unet: Multi-Modality Cell Segmentation based on nnU-Net Pipeline
Adaptive Bayesian Sampling with Monte Carlo EM
Beyond Individualized Recourse: Interpretable and Interactive Summaries of Actionable Recourses
Overcoming Catastrophic Forgetting by Incremental Moment Matching
Guided Adversarial Attack for Evaluating and Enhancing Adversarial Defenses
Continuous Meta-Learning without Tasks
Found Graph Data and Planted Vertex Covers
Transferable Graph Optimizers for ML Compilers
Learning Linear Causal Representations from Interventions under General Nonlinear Mixing
Voxel-based 3D Detection and Reconstruction of Multiple Objects from a Single Image
Hyper-opinion Evidential Deep Learning for Out-of-Distribution Detection
TensorNet: Cartesian Tensor Representations for Efficient Learning of Molecular Potentials
Goal-conditioned Offline Planning from Curious Exploration
Nonparametric Classification on Low Dimensional Manifolds using Overparameterized Convolutional Residual Networks
Smooth, exact rotational symmetrization for deep learning on point clouds
Infusing Synthetic Data with Real-World Patterns for Zero-Shot Material State Segmentation
A Simple Practical Accelerated Method for Finite Sums
Graph Neural Flows for Unveiling Systemic Interactions Among Irregularly Sampled Time Series
Accelerated On-Device Forward Neural Network Training with Module-Wise Descending Asynchronism
Strategic Behavior is Bliss: Iterative Voting Improves Social Welfare
STXD: Structural and Temporal Cross-Modal Distillation for Multi-View 3D Object Detection
Learning from queries for maximum information gain in imperfectly learnable problems
Multi-stage Convex Relaxation for Learning with Sparse Regularization
Adversarially Robust Learning: A Generic Minimax Optimal Learner and Characterization
Neural Lad: A Neural Latent Dynamics Framework for Times Series Modeling
Variational Memory Addressing in Generative Models
SAPA: Similarity-Aware Point Affiliation for Feature Upsampling
A Computationally Efficient Method for Estimating Semi Parametric Regression Functions
Joint Entropy Search For Maximally-Informed Bayesian Optimization
Adapting to Misspecification in Contextual Bandits
On the Expressiveness of Approximate Inference in Bayesian Neural Networks
Self-Adaptive Motion Tracking against On-body Displacement of Flexible Sensors
On the Generalizability and Predictability of Recommender Systems
Metropolis Sampling for Constrained Diffusion Models
A Comprehensive Linear Speedup Analysis for Asynchronous Stochastic Parallel Optimization from Zeroth-Order to First-Order
Embodied Scene-aware Human Pose Estimation
On Model Calibration for Long-Tailed Object Detection and Instance Segmentation
Convergence for score-based generative modeling with polynomial complexity
Objective and efficient inference for couplings in neuronal networks
POLY-HOOT: Monte-Carlo Planning in Continuous Space MDPs with Non-Asymptotic Analysis
Conditional Outcome Equivalence: A Quantile Alternative to CATE
Robustness of classifiers: from adversarial to random noise
Optimal Asset Allocation using Adaptive Dynamic Programming
Mechanisms for Neuromodulation of Biological Neural Networks
Stars: Tera-Scale Graph Building for Clustering and Learning
Estimating the Location and Orientation of Complex, Correlated Neural Activity using MEG
Simple, Distributed, and Accelerated Probabilistic Programming
The Missing Invariance Principle found - the Reciprocal Twin of Invariant Risk Minimization
HF-NeuS: Improved Surface Reconstruction Using High-Frequency Details
Embrace the Gap: VAEs Perform Independent Mechanism Analysis
Slack-Free Spiking Neural Network Formulation for Hypergraph Minimum Vertex Cover
FlexMol: A Flexible Toolkit for Benchmarking Molecular Relational Learning
ClashEval: Quantifying the tug-of-war between an LLM's internal prior and external evidence
Invariant Anomaly Detection under Distribution Shifts: A Causal Perspective
Joint Tracking of Pose, Expression, and Texture using Conditionally Gaussian Filters
Data Clustering by Markovian Relaxation and the Information Bottleneck Method
Dynamic Bottleneck for Robust Self-Supervised Exploration
XES3G5M: A Knowledge Tracing Benchmark Dataset with Auxiliary Information
Towards Open-World Feature Extrapolation: An Inductive Graph Learning Approach
Relational Reasoning via Set Transformers: Provable Efficiency and Applications to MARL
Langevin Unlearning: A New Perspective of Noisy Gradient Descent for Machine Unlearning
A Multi-Task Benchmark for Korean Legal Language Understanding and Judgement Prediction
Non-asymptotic Analysis of Stochastic Methods for Non-Smooth Non-Convex Regularized Problems
Correlation Codes in Neuronal Populations
Optimal approximation using complex-valued neural networks
Language Without Borders: A Dataset and Benchmark for Code-Switching Lip Reading
WFCRL: A Multi-Agent Reinforcement Learning Benchmark for Wind Farm Control
Gradient Descent Is Optimal Under Lower Restricted Secant Inequality And Upper Error Bound
Task-Agnostic Online Reinforcement Learning with an Infinite Mixture of Gaussian Processes
Efficient Approaches to Gaussian Process Classification
How Does the Brain Represent Visual Scenes? A Neuromagnetic Scene Categorization Study
Linearly Decomposing and Recomposing Vision Transformers for Diverse-Scale Models
Is A Picture Worth A Thousand Words? Delving Into Spatial Reasoning for Vision Language Models
Convergence of Actor-Critic with Multi-Layer Neural Networks
Foundations of Multivariate Distributional Reinforcement Learning
Kernel similarity matching with Hebbian networks
Synthetic Benchmarks for Scientific Research in Explainable Machine Learning
Towards Biologically Plausible Convolutional Networks
Bayesian Meta-Learning for the Few-Shot Setting via Deep Kernels
Analyzing Generalization of Neural Networks through Loss Path Kernels
Near-Optimal Collaborative Learning in Bandits
Generalizing Tree Probability Estimation via Bayesian Networks
Non-asymptotic Global Convergence Analysis of BFGS with the Armijo-Wolfe Line Search
Optimal Sketching for Kronecker Product Regression and Low Rank Approximation
Dialog-based Interactive Image Retrieval
New Criteria and a New Algorithm for Learning in Multi-Agent Systems
Bipartite expander Hopfield networks as self-decoding high-capacity error correcting codes
Segment Anything in 3D with NeRFs
Gradient Estimation with Discrete Stein Operators
MALT Powers Up Adversarial Attacks
MABSplit: Faster Forest Training Using Multi-Armed Bandits
Memorization and Optimization in Deep Neural Networks with Minimum Over-parameterization
Probabilistic Graph Rewiring via Virtual Nodes
An ensemble diversity approach to supervised binary hashing
Towards the Transferability of Rewards Recovered via Regularized Inverse Reinforcement Learning
No "Zero-Shot" Without Exponential Data: Pretraining Concept Frequency Determines Multimodal Model Performance
Capacity Bounded Differential Privacy
Probabilistic Inference in Human Sensorimotor Processing
Knowledge-inspired 3D Scene Graph Prediction in Point Cloud
Diffeomorphic Dimensionality Reduction
Survival Instinct in Offline Reinforcement Learning
Joint Entropy Search for Multi-Objective Bayesian Optimization
Predicting Event Memorability from Contextual Visual Semantics
Neuropathic Pain Diagnosis Simulator for Causal Discovery Algorithm Evaluation
WAGLE: Strategic Weight Attribution for Effective and Modular Unlearning in Large Language Models
Doubly-Robust Self-Training
Modeling Natural Sounds with Modulation Cascade Processes
Individualized ROI Optimization via Maximization of Group-wise Consistency of Structural and Functional Profiles
The surprising efficiency of temporal difference learning for rare event prediction
Hyperspherical Prototype Networks
Learning to Decode: Reinforcement Learning for Decoding of Sparse Graph-Based Channel Codes
Supervising the Transfer of Reasoning Patterns in VQA
Diffusion Schrödinger Bridge with Applications to Score-Based Generative Modeling
On the Interpretability of Regularisation for Neural Networks Through Model Gradient Similarity
Spot the Difference: Detection of Topological Changes via Geometric Alignment
Learning the Number of Neurons in Deep Networks
A Latent Source Model for Online Collaborative Filtering
Teaching Multiple Concepts to a Forgetful Learner
Mind the Gap: A Causal Perspective on Bias Amplification in Prediction & Decision-Making
Conditional Swap Regret and Conditional Correlated Equilibrium
Identification and Estimation of Joint Probabilities of Potential Outcomes in Observational Studies with Covariate Information
Spike-Based Compared to Rate-Based Hebbian Learning
Probabilistic Curve Learning: Coulomb Repulsion and the Electrostatic Gaussian Process
Autonomous Driving with Spiking Neural Networks
VAST: A Vision-Audio-Subtitle-Text Omni-Modality Foundation Model and Dataset
InfoGAN: Interpretable Representation Learning by Information Maximizing Generative Adversarial Nets
SplitNeRF: Split Sum Approximation Neural Field for Joint Geometry, Illumination, and Material Estimation
Noise and the two-thirds power Law
Plan To Predict: Learning an Uncertainty-Foreseeing Model For Model-Based Reinforcement Learning
Probabilistic Inference with Algebraic Constraints: Theoretical Limits and Practical Approximations
CSAW-M: An Ordinal Classification Dataset for Benchmarking Mammographic Masking of Cancer
Secret Collusion among AI Agents: Multi-Agent Deception via Steganography
Neural Bridge Sampling for Evaluating Safety-Critical Autonomous Systems
FourierNets enable the design of highly non-local optical encoders for computational imaging
Repeated Inverse Reinforcement Learning
OBELICS: An Open Web-Scale Filtered Dataset of Interleaved Image-Text Documents
Safe Opponent-Exploitation Subgame Refinement
Online Markov Decision Processes under Bandit Feedback
SWE-agent: Agent-Computer Interfaces Enable Automated Software Engineering
TwiBot-22: Towards Graph-Based Twitter Bot Detection
DarkSAM: Fooling Segment Anything Model to Segment Nothing
Control Variates for Slate Off-Policy Evaluation
Synthesis of MCMC and Belief Propagation
Oracle Inequalities for Model Selection in Offline Reinforcement Learning
A class of network models recoverable by spectral clustering
Learning with Operator-valued Kernels in Reproducing Kernel Krein Spaces
SoundCam: A Dataset for Finding Humans Using Room Acoustics
Structural equations and divisive normalization for energy-dependent component analysis
Learning to Understand: Identifying Interactions via the Möbius Transform
Fast amortized inference of neural activity from calcium imaging data with variational autoencoders
Personalized Instance-based Navigation Toward User-Specific Objects in Realistic Environments
Self-paced Contrastive Learning with Hybrid Memory for Domain Adaptive Object Re-ID
SCube: Instant Large-Scale Scene Reconstruction using VoxSplats
Pluralistic Image Completion with Gaussian Mixture Models
Adversarial Robustness without Adversarial Training: A Teacher-Guided Curriculum Learning Approach
A polynomial-time algorithm for learning nonparametric causal graphs
The Role of Global Labels in Few-Shot Classification and How to Infer Them
On the Convergence of Stochastic Gradient MCMC Algorithms with High-Order Integrators
Hiding Images in Plain Sight: Deep Steganography
Off-Policy Interval Estimation with Lipschitz Value Iteration
ShiftAddNet: A Hardware-Inspired Deep Network
A Neural Implementation of the Kalman Filter
Private Testing of Distributions via Sample Permutations
Structure Regularization for Structured Prediction
Adaptive Influence Maximization with Myopic Feedback
Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks
Large-scale L-BFGS using MapReduce
Stochastic Online Linear Regression: the Forward Algorithm to Replace Ridge
Blind Separation of Delayed and Convolved Sources
Ultrahyperbolic Representation Learning
Bayesian nonparametric (non-)renewal processes for analyzing neural spike train variability
Information Measure Based Skeletonisation
Bounded Finite State Controllers
In Defense of Softmax Parametrization for Calibrated and Consistent Learning to Defer
Bayesian inference as iterated random functions with applications to sequential inference in graphical models
Towards Improving Calibration in Object Detection Under Domain Shift
Unsupervised Object-Level Representation Learning from Scene Images
An efficient graph generative model for navigating ultra-large combinatorial synthesis libraries
Learning Taxonomies by Dependence Maximization
Cherry on Top: Parameter Heterogeneity and Quantization in Large Language Models
Efficient Variational Inference for Sparse Deep Learning with Theoretical Guarantee
Two-Target Algorithms for Infinite-Armed Bandits with Bernoulli Rewards
Modular Networks: Learning to Decompose Neural Computation
Brain Diffusion for Visual Exploration: Cortical Discovery using Large Scale Generative Models
OpenFWI: Large-scale Multi-structural Benchmark Datasets for Full Waveform Inversion
Aggregating Capacity in FL through Successive Layer Training for Computationally-Constrained Devices
Neural Networks: The Early Days
Hierarchical Memory-Based Reinforcement Learning
Subquadratic High-Dimensional Hierarchical Clustering
Towards Label-free Scene Understanding by Vision Foundation Models
Random Projections for Manifold Learning
Shaving Weights with Occam's Razor: Bayesian Sparsification for Neural Networks using the Marginal Likelihood
Global seismic monitoring as probabilistic inference
Near-Optimal MAP Inference for Determinantal Point Processes
Deep inference of latent dynamics with spatio-temporal super-resolution using selective backpropagation through time
Learning Human Action Recognition Representations Without Real Humans
Adaptive Principal Component Regression with Applications to Panel Data
Joint Modeling of Visual Objects and Relations for Scene Graph Generation
On Bootstrapping the ROC Curve
Toward Real Ultra Image Segmentation: Leveraging Surrounding Context to Cultivate General Segmentation Model
KALM: Knowledgeable Agents by Offline Reinforcement Learning from Large Language Model Rollouts
Battle of the Backbones: A Large-Scale Comparison of Pretrained Models across Computer Vision Tasks
Local Anti-Concentration Class: Logarithmic Regret for Greedy Linear Contextual Bandit
Memorize What Matters: Emergent Scene Decomposition from Multitraverse
Efficient and Accurate Lp-Norm Multiple Kernel Learning
SAMURAI: Shape And Material from Unconstrained Real-world Arbitrary Image collections
Learning Auctions with Robust Incentive Guarantees
American Stories: A Large-Scale Structured Text Dataset of Historical U.S. Newspapers
Advances in Neural Information Processing Systems 17 [Neural Information Processing Systems, NIPS 2004, December 13-18, 2004, Vancouver, British Columbia, Canada]
Propensity Score Alignment of Unpaired Multimodal Data
Covert Attention as a Paradigm for Subject-Independent Brain-Computer Interfacing
Deep Learning without Poor Local Minima
SQ Lower Bounds for Non-Gaussian Component Analysis with Weaker Assumptions
Overcoming Language Priors in Visual Question Answering with Adversarial Regularization
Structured Prediction for Conditional Meta-Learning
Sinkhorn Natural Gradient for Generative Models
Knowledge-Based Support Vector Machine Classifiers
CorDA: Context-Oriented Decomposition Adaptation of Large Language Models for Task-Aware Parameter-Efficient Fine-tuning
Meta-Learning Dynamics Forecasting Using Task Inference
A Complete Recipe for Stochastic Gradient MCMC
Efficiency Ordering of Stochastic Gradient Descent
FIND: A Function Description Benchmark for Evaluating Interpretability Methods
Near-Optimal Distributed Minimax Optimization under the Second-Order Similarity
A Local Method for Satisfying Interventional Fairness with Partially Known Causal Graphs
Learning Noisy Halfspaces with a Margin: Massart is No Harder than Random
Time-Sequential Self-Organization of Hierarchical Neural Networks
StrokeRehab: A Benchmark Dataset for Sub-second Action Identification
FiLM-Ensemble: Probabilistic Deep Learning via Feature-wise Linear Modulation
Automated Discovery of Adaptive Attacks on Adversarial Defenses
FactorizePhys: Matrix Factorization for Multidimensional Attention in Remote Physiological Sensing
Conformalized Multiple Testing after Data-dependent Selection
Dynamics of Supervised and Reinforcement Learning in the Non-Linear Perceptron
Incremental Parsing by Modular Recurrent Connectionist Networks
Label-efficient Segmentation via Affinity Propagation
On the Impact of Feature Heterophily on Link Prediction with Graph Neural Networks
Stylized Dialogue Generation with Multi-Pass Dual Learning
Can we have it all? On the Trade-off between Spatial and Adversarial Robustness of Neural Networks
Provable Online CP/PARAFAC Decomposition of a Structured Tensor via Dictionary Learning
Riemannian SVRG: Fast Stochastic Optimization on Riemannian Manifolds
Catch-A-Waveform: Learning to Generate Audio from a Single Short Example
Vulnerabilities in Video Quality Assessment Models: The Challenge of Adversarial Attacks
From Batch to Transductive Online Learning
Practical Bayesian Algorithm Execution via Posterior Sampling
Tuning Mixed Input Hyperparameters on the Fly for Efficient Population Based AutoRL
STDP enables spiking neurons to detect hidden causes of their inputs
Stable Bias: Evaluating Societal Representations in Diffusion Models
Effects of Spatial and Temporal Contiguity on the Acquisition of Spatial Information
Textually Pretrained Speech Language Models
Chasing Fairness Under Distribution Shift: A Model Weight Perturbation Approach
Representation Learning Beyond Linear Prediction Functions
Provably (More) Sample-Efficient Offline RL with Options
Particle Gibbs for Infinite Hidden Markov Models
MissDAG: Causal Discovery in the Presence of Missing Data with Continuous Additive Noise Models
Conditioning and Processing: Techniques to Improve Information-Theoretic Generalization Bounds
Adaptive Image Quality Assessment via Teaching Large Multimodal Model to Compare
Scalable Membership Inference Attacks via Quantile Regression
VF-PS: How to Select Important Participants in Vertical Federated Learning, Efficiently and Securely?
An Efficient Doubly-Robust Test for the Kernel Treatment Effect
Attend, Infer, Repeat: Fast Scene Understanding with Generative Models
Best-First Model Merging for Dynamic Learning and Recognition
Fast Large-scale Mixture Modeling with Component-specific Data Partitions
DetNAS: Backbone Search for Object Detection
Framing RNN as a kernel method: A neural ODE approach
Attend and Decode: 4D fMRI Task State Decoding Using Attention Models
On Correctness of Automatic Differentiation for Non-Differentiable Functions
SpaFL: Communication-Efficient Federated Learning With Sparse Models And Low Computational Overhead
On the spectral bias of two-layer linear networks
Online Passive-Aggressive Algorithms
Reinforcement-Enhanced Autoregressive Feature Transformation: Gradient-steered Search in Continuous Space for Postfix Expressions
Accelerating Molecular Graph Neural Networks via Knowledge Distillation
Learning from higher-order correlations, efficiently: hypothesis tests, random features, and neural networks
Asymmetric LSH (ALSH) for Sublinear Time Maximum Inner Product Search (MIPS)
Con4m: Context-aware Consistency Learning Framework for Segmented Time Series Classification
Nearly Optimal Best-of-Both-Worlds Algorithms for Online Learning with Feedback Graphs
REBAR: Low-variance, unbiased gradient estimates for discrete latent variable models
Joint Autoregressive and Hierarchical Priors for Learned Image Compression
Gradients for Retinotectal Mapping
StoryDiffusion: Consistent Self-Attention for Long-Range Image and Video Generation
Imagine the Unseen World: A Benchmark for Systematic Generalization in Visual World Models
Learning the Optimal Policy for Balancing Short-Term and Long-Term Rewards
Error Discovery By Clustering Influence Embeddings
Optimal Variance Control of the Score-Function Gradient Estimator for Importance-Weighted Bounds
Temporal Difference Based Actor Critic Learning - Convergence and Neural Implementation
GAMap: Zero-Shot Object Goal Navigation with Multi-Scale Geometric-Affordance Guidance
Retrospective Adversarial Replay for Continual Learning
General E(2)-Equivariant Steerable CNNs
Automatic Capacity Tuning of Very Large VC-Dimension Classifiers
The Pursuit of Human Labeling: A New Perspective on Unsupervised Learning
Certified Robustness via Dynamic Margin Maximization and Improved Lipschitz Regularization
AFBench: A Large-scale Benchmark for Airfoil Design
Measuring Sample Quality with Stein's Method
Explainable Brain Age Prediction using coVariance Neural Networks
NeuroSchedule: A Novel Effective GNN-based Scheduling Method for High-level Synthesis
Sim2Real-Fire: A Multi-modal Simulation Dataset for Forecast and Backtracking of Real-world Forest Fire
fMRI-Based Inter-Subject Cortical Alignment Using Functional Connectivity
Improving Simple Models with Confidence Profiles
Decentralized Q-learning in Zero-sum Markov Games
Kernel Stein Tests for Multiple Model Comparison
Brain-like Flexible Visual Inference by Harnessing Feedback Feedforward Alignment
Sharpness-Aware Training for Free
Findings of the Second AmericasNLP Competition on Speech-to-Text Translation
Learning Structure from the Ground up - Hierarchical Representation Learning by Chunking
ProSST: Protein Language Modeling with Quantized Structure and Disentangled Attention
Do Deep Neural Networks Suffer from Crowding?
Flow Matching for Scalable Simulation-Based Inference
TopoSRL: Topology preserving self-supervised Simplicial Representation Learning
Learning-Augmented Priority Queues
Pretraining Codomain Attention Neural Operators for Solving Multiphysics PDEs
Modeling Nonlinear Dependencies in Natural Images using Mixture of Laplacian Distribution
Spatiotemporal Coupling and Scaling of Natural Images and Human Visual Sensitivities
Metis: Understanding and Enhancing In-Network Regular Expressions
SuperDeepFool: a new fast and accurate minimal adversarial attack
Domain Adaptation with Conditional Distribution Matching and Generalized Label Shift
Neuronal Regulation Implements Efficient Synaptic Pruning
Benchmarking Data-driven Surrogate Simulators for Artificial Electromagnetic Materials
Deep Subspace Clustering Networks
The Softmax Nonlinearity: Derivation Using Statistical Mechanics and Useful Properties as a Multiterminal Analog Circuit Element
Real-world Image Dehazing with Coherence-based Pseudo Labeling and Cooperative Unfolding Network
Neural Frailty Machine: Beyond proportional hazard assumption in neural survival regressions
Unleashing Region Understanding in Intermediate Layers for MLLM-based Referring Expression Generation
Modelling transcriptional regulation using Gaussian Processes
GeoPhy: Differentiable Phylogenetic Inference via Geometric Gradients of Tree Topologies
Center Smoothing: Certified Robustness for Networks with Structured Outputs
A Boundary Hunting Radial Basis Function Classifier which Allocates Centers Constructively