yusuke1997/dblp-id-title huggingface dataset:
Understanding Interlocking Dynamics of Cooperative Rationalization
Grassmann Manifold Flows for Stable Shape Generation
Relative Uncertainty Learning for Facial Expression Recognition
From Stochastic Planning to Marginal MAP
Natural Policy Gradient Primal-Dual Method for Constrained Markov Decision Processes
Mutual Information Estimation via f-Divergence and Data Derangements
Learning dynamic polynomial proofs
Two-Layer Feature Reduction for Sparse-Group Lasso via Decomposition of Convex Sets
Deep Learning for Precipitation Nowcasting: A Benchmark and A New Model
Weakly Supervised Representation Learning with Sparse Perturbations
ELF: An Extensive, Lightweight and Flexible Research Platform for Real-time Strategy Games
Learning Dense 3D Correspondence
A Toolkit for Reliable Benchmarking and Research in Multi-Objective Reinforcement Learning
POMDP Planning for Object Search in Partially Unknown Environment
Regularisation in Sequential Learning Algorithms
CommonScenes: Generating Commonsense 3D Indoor Scenes with Scene Graphs
TTOpt: A Maximum Volume Quantized Tensor Train-based Optimization and its Application to Reinforcement Learning
Margin Analysis of the LVQ Algorithm
Invariant Common Spatial Patterns: Alleviating Nonstationarities in Brain-Computer Interfacing
One Loss for All: Deep Hashing with a Single Cosine Similarity based Learning Objective
Shared Space Transfer Learning for analyzing multi-site fMRI data
Learning ReLUs via Gradient Descent
Flipped Classroom: Aligning Teacher Attention with Student in Generalized Category Discovery
A Computational Separation between Private Learning and Online Learning
Online PAC-Bayes Learning
Dissecting the Failure of Invariant Learning on Graphs
A Phase Space Approach to Minimax Entropy Learning and the Minutemax Approximations
CodeCMR: Cross-Modal Retrieval For Function-Level Binary Source Code Matching
ReGS: Reference-based Controllable Scene Stylization with Gaussian Splatting
What type of inference is planning?
Artsheets for Art Datasets
Hybrid Models for Learning to Branch
Alleviating "Posterior Collapse" in Deep Topic Models via Policy Gradient
Exponentially Improving the Complexity of Simulating the Weisfeiler-Lehman Test with Graph Neural Networks
PAD: A Dataset and Benchmark for Pose-agnostic Anomaly Detection
Robustness and risk-sensitivity in Markov decision processes
Watch out! Motion is Blurring the Vision of Your Deep Neural Networks
I Don't Know: Explicit Modeling of Uncertainty with an [IDK] Token
A Sampled Texture Prior for Image Super-Resolution
Discovering and Overcoming Limitations of Noise-engineered Data-free Knowledge Distillation
Meta-Reinforced Synthetic Data for One-Shot Fine-Grained Visual Recognition
The Forget-me-not Process
Modularity in the motor system: decomposition of muscle patterns as combinations of time-varying synergies
Introducing Routing Uncertainty in Capsule Networks
Referencing Where to Focus: Improving Visual Grounding with Referential Query
General Proximal Incremental Aggregated Gradient Algorithms: Better and Novel Results under General Scheme
The Feature Speed Formula: a flexible approach to scale hyper-parameters of deep neural networks
Using Machine Learning to Break Visual Human Interaction Proofs (HIPs)
Meta-Gradient Reinforcement Learning with an Objective Discovered Online
Coresets for Wasserstein Distributionally Robust Optimization Problems
Attack-Aware Noise Calibration for Differential Privacy
Fast and Flexible Temporal Point Processes with Triangular Maps
Simple Regression Models
Visual Dynamics: Probabilistic Future Frame Synthesis via Cross Convolutional Networks
Dual-Resolution Correspondence Networks
Hashing Algorithms for Large-Scale Learning
Implicit variance regularization in non-contrastive SSL
Slimmed Asymmetrical Contrastive Learning and Cross Distillation for Lightweight Model Training
Do Counterfactually Fair Image Classifiers Satisfy Group Fairness? - A Theoretical and Empirical Study
The probability flow ODE is provably fast
Combining Human Predictions with Model Probabilities via Confusion Matrices and Calibration
Mutual Information Regularized Offline Reinforcement Learning
Divide-and-Conquer Posterior Sampling for Denoising Diffusion priors
Human Expertise in Algorithmic Prediction
Identifiable Shared Component Analysis of Unpaired Multimodal Mixtures
Self-Interpretable Model with Transformation Equivariant Interpretation
Reasoning about Uncertainties in Discrete-Time Dynamical Systems using Polynomial Forms
Invariant subspaces and PCA in nearly matrix multiplication time
Heterogeneous Multi-output Gaussian Process Prediction
Gradient Descent on Two-layer Nets: Margin Maximization and Simplicity Bias
Towards Practical Few-shot Query Sets: Transductive Minimum Description Length Inference
Meta-Learning the Search Distribution of Black-Box Random Search Based Adversarial Attacks
Video-Mined Task Graphs for Keystep Recognition in Instructional Videos
Scalable Model Selection for Belief Networks
On the Accuracy of Self-Normalized Log-Linear Models
Exploring and Exploiting the Asymmetric Valley of Deep Neural Networks
Ensembling Graph Predictions for AMR Parsing
Text-to-Image Diffusion Models are Zero Shot Classifiers
EAGER: Asking and Answering Questions for Automatic Reward Shaping in Language-guided RL
Regressive Virtual Metric Learning
Local Identifiability of Deep ReLU Neural Networks: the Theory
A Data-Centric Perspective on Evaluating Machine Learning Models for Tabular Data
Feedback Detection for Live Predictors
Contextual Modulation of Target Saliency
The CPD Data Set: Personnel, Use of Force, and Complaints in the Chicago Police Department
Computational Differences between Asymmetrical and Symmetrical Networks
Modeling the spacing effect in sequential category learning
Robust Prompt Optimization for Defending Language Models Against Jailbreaking Attacks
An Adaptive Algorithm for Learning with Unknown Distribution Drift
Self-Weighted Contrastive Learning among Multiple Views for Mitigating Representation Degeneration
GENESIS-V2: Inferring Unordered Object Representations without Iterative Refinement
Beyond Exponential Graph: Communication-Efficient Topologies for Decentralized Learning via Finite-time Convergence
Correlation and Interpolation Networks for Real-time Expression Analysis/Synthesis
Higher-Rank Irreducible Cartesian Tensors for Equivariant Message Passing
An Empirical Analysis of Domain Adaptation Algorithms for Genomic Sequence Analysis
Efficient Convex Completion of Coupled Tensors using Coupled Nuclear Norms
Simulation and Measurement of the Electric Fields Generated by Weakly Electric Fish
Testing Probabilistic Circuits
Cross-modal Active Complementary Learning with Self-refining Correspondence
Cross-video Identity Correlating for Person Re-identification Pre-training
Curriculum Learning With Infant Egocentric Videos
Class Distribution Shifts in Zero-Shot Learning: Learning Robust Representations
MGNNI: Multiscale Graph Neural Networks with Implicit Layers
Dual-Diffusion for Binocular 3D Human Pose Estimation
Local Supervised Learning through Space Partitioning
Extracting regions of interest from biological images with convolutional sparse block coding
Trading Off Resource Budgets For Improved Regret Bounds
Flows for simultaneous manifold learning and density estimation
SlimGPT: Layer-wise Structured Pruning for Large Language Models
Reusable Slotwise Mechanisms
Development of Hybrid Systems: Interfacing a Silicon Neuron to a Leech Heart Interneuron
Unsupervised Learning of Dense Visual Representations
MAGIS: LLM-Based Multi-Agent Framework for GitHub Issue Resolution
SPACE: Single-round Participant Amalgamation for Contribution Evaluation in Federated Learning
A multi-agent reinforcement learning model of common-pool resource appropriation
A versatile informative diffusion model for single-cell ATAC-seq data generation and analysis
WeightedSHAP: analyzing and improving Shapley based feature attributions
PointNeXt: Revisiting PointNet++ with Improved Training and Scaling Strategies
Learning vehicular dynamics, with application to modeling helicopters
DropMax: Adaptive Variational Softmax
Sparse Greedy Minimax Probability Machine Classification
Code Repair with LLMs gives an Exploration-Exploitation Tradeoff
A Stochastic Linearized Augmented Lagrangian Method for Decentralized Bilevel Optimization
An Exponential Improvement on the Memorization Capacity of Deep Threshold Networks
Mixed Samples as Probes for Unsupervised Model Selection in Domain Adaptation
Inference for the Generalization Error
Decision Stacks: Flexible Reinforcement Learning via Modular Generative Models
Fast Sampling-Based Inference in Balanced Neuronal Networks
Sound and Complete Verification of Polynomial Networks
Ensemble Learning and Linear Response Theory for ICA
Regret Bounds for Information-Directed Reinforcement Learning
Spreading Activation over Distributed Microfeatures
A gradient sampling method with complexity guarantees for Lipschitz functions in high and low dimensions
Instance-Based Uncertainty Estimation for Gradient-Boosted Regression Trees
Sample Complexity Bounds for Active Ranking from Multi-wise Comparisons
Generative Adversarial Model-Based Optimization via Source Critic Regularization
Learn What Not to Learn: Action Elimination with Deep Reinforcement Learning
Joint Analysis of Time-Evolving Binary Matrices and Associated Documents
On The Structure of Parametric Tournaments with Application to Ranking from Pairwise Comparisons
The Cerebellum Chip: an Analog VLSI Implementation of a Cerebellar Model of Classical Conditioning
Clustering Signed Networks with the Geometric Mean of Laplacians
Tartarus: A Benchmarking Platform for Realistic And Practical Inverse Molecular Design
On the Double Descent of Random Features Models Trained with SGD
Coastal Navigation with Mobile Robots
VLSI Implementation of Cortical Visual Motion Detection Using an Analog Neural Computer
Object Reprojection Error (ORE): Camera pose benchmarks from lightweight tracking annotations
OOD-MAML: Meta-Learning for Few-Shot Out-of-Distribution Detection and Classification
Contrastive Learning from Pairwise Measurements
Cascaded Text Generation with Markov Transformers
Outcomes of the Equivalence of Adaptive Ridge with Least Absolute Shrinkage
A Non-parametric Learning Method for Confidently Estimating Patient's Clinical State and Dynamics
Fixing two weaknesses of the Spectral Method
Bilevel Distance Metric Learning for Robust Image Recognition
Time/Accuracy Tradeoffs for Learning a ReLU with respect to Gaussian Marginals
Fault-Tolerant Federated Reinforcement Learning with Theoretical Guarantee
Uniform-PAC Bounds for Reinforcement Learning with Linear Function Approximation
Understanding Neural Network Binarization with Forward and Backward Proximal Quantizers
Variational Policy Gradient Method for Reinforcement Learning with General Utilities
Context-Dependent Classes in a Hybrid Recurrent Network-HMM Speech Recognition System
Robust Sparse Principal Component Regression under the High Dimensional Elliptical Model
Hunt For The Unique, Stable, Sparse And Fast Feature Learning On Graphs
On Embeddings for Numerical Features in Tabular Deep Learning
Locality-Sensitive Hashing for f-Divergences: Mutual Information Loss and Beyond
A Decision-Language Model (DLM) for Dynamic Restless Multi-Armed Bandit Tasks in Public Health
Assessing Fairness in the Presence of Missing Data
Training Factor Graphs with Reinforcement Learning for Efficient MAP Inference
Implications of Recursive Distributed Representations
Improving Adversarial Robustness via Information Bottleneck Distillation
On the Theory of Transfer Learning: The Importance of Task Diversity
Instance-Specific Asymmetric Sensitivity in Differential Privacy
Learning Joint Statistical Models for Audio-Visual Fusion and Segregation
On the Calibration of Multiclass Classification with Rejection
Taming Cross-Domain Representation Variance in Federated Prototype Learning with Heterogeneous Data Domains
Scalable DBSCAN with Random Projections
Parametric Complexity Bounds for Approximating PDEs with Neural Networks
On the Frequency Bias of Generative Models
Your Out-of-Distribution Detection Method is Not Robust!
Hierarchical Open-vocabulary Universal Image Segmentation
Gradient Estimation with Stochastic Softmax Tricks
Deep Equilibrium Algorithmic Reasoning
Trading Computation for Communication: Distributed Stochastic Dual Coordinate Ascent
Phonetic Speaker Recognition with Support Vector Machines
Visually Grounded Interaction and Language (ViGIL), NeurIPS 2019 Workshop, Vancouver, Canada, December 13, 2019
Adaptive Privacy Composition for Accuracy-first Mechanisms
Bandit Social Learning under Myopic Behavior
Treatment of Statistical Estimation Problems in Randomized Smoothing for Adversarial Robustness
Diffusion Models With Learned Adaptive Noise
Residual Relaxation for Multi-view Representation Learning
Direct Memory Access Using Two Cues
cPAPERS: A Dataset of Situated and Multimodal Interactive Conversations in Scientific Papers
SpecTr: Fast Speculative Decoding via Optimal Transport
Instance-optimality in differential privacy via approximate inverse sensitivity mechanisms
Target alignment in truncated kernel ridge regression
Cross Aggregation Transformer for Image Restoration
RL on Incorrect Synthetic Data Scales the Efficiency of LLM Math Reasoning by Eight-Fold
Efficient Adversarial Training in LLMs with Continuous Attacks
A Variational Edge Partition Model for Supervised Graph Representation Learning
Towards Exact Gradient-based Training on Analog In-memory Computing
Autoencoders that don't overfit towards the Identity
Graph Edit Distance with General Costs Using Neural Set Divergence
You Never Cluster Alone
Private and Communication-Efficient Algorithms for Entropy Estimation
Trajectory Flow Matching with Applications to Clinical Time Series Modelling
On the Relationship Between Relevance and Conflict in Online Social Link Recommendations
The power of feature clustering: An application to object detection
Multifaceted Uncertainty Estimation for Label-Efficient Deep Learning
InfoPrompt: Information-Theoretic Soft Prompt Tuning for Natural Language Understanding
Sparse Embedded k-Means Clustering
$\epsilon$-Softmax: Approximating One-Hot Vectors for Mitigating Label Noise
Efficient Match Kernel between Sets of Features for Visual Recognition
Using Convolutional Neural Networks to Recognize Rhythm Stimuli from Electroencephalography Recordings
Boosting Algorithms for Maximizing the Soft Margin
Neuron with Steady Response Leads to Better Generalization
Provably Efficient Reinforcement Learning with Kernel and Neural Function Approximations
A scalable end-to-end Gaussian process adapter for irregularly sampled time series classification
Achieving Tractable Minimax Optimal Regret in Average Reward MDPs
WaterMax: breaking the LLM watermark detectability-robustness-quality trade-off
A Lagrangian Approach to Fixed Points
Efficient multi-prompt evaluation of LLMs
Mixture Weight Estimation and Model Prediction in Multi-source Multi-target Domain Adaptation
Transformation Invariance in Pattern Recognition-Tangent Distance and Tangent Propagation
Optimal decision-making with time-varying evidence reliability
Asymptotics of Gaussian Regularized Least Squares
CS-Shapley: Class-wise Shapley Values for Data Valuation in Classification
Impression learning: Online representation learning with synaptic plasticity
A Complexity-Distortion Approach to Joint Pattern Alignment
Strong and Precise Modulation of Human Percepts via Robustified ANNs
Remix-DiT: Mixing Diffusion Transformers for Multi-Expert Denoising
Multi-Objective Deep Learning with Adaptive Reference Vectors
A Swiss Army Knife for Heterogeneous Federated Learning: Flexible Coupling via Trace Norm
Attention-Based Models for Speech Recognition
Gradient-based Hyperparameter Optimization Over Long Horizons
Learning Saccadic Eye Movements Using Multiscale Spatial Filters
A theory of neural integration in the head-direction system
Towards Robust Bisimulation Metric Learning
Differentiable Augmentation for Data-Efficient GAN Training
Iterative Teacher-Aware Learning
Zero-shot Learning with Semantic Output Codes
Robustness to Unbounded Smoothness of Generalized SignSGD
Bayesian Co-Training
Subspace Clustering via Tangent Cones
Adversarial vulnerability for any classifier
Graph Matching for Shape Retrieval
Hypervolume Maximization: A Geometric View of Pareto Set Learning
Asymptotically Optimal Exact Minibatch Metropolis-Hastings
Neural Cover Selection for Image Steganography
Interactive Corpora Visualization for 60 Years of AI Research
Orthogonal Matching Pursuit From Noisy Random Measurements: A New Analysis
Train Once, Get a Family: State-Adaptive Balances for Offline-to-Online Reinforcement Learning
HiNeRV: Video Compression with Hierarchical Encoding-based Neural Representation
A distributional simplicity bias in the learning dynamics of transformers
Learning Treewidth-Bounded Bayesian Networks with Thousands of Variables
A Kernel Statistical Test of Independence
Traffic4cast at NeurIPS 2021 - Temporal and Spatial Few-Shot Transfer Learning in Gridded Geo-Spatial Processes
Evolving Standardization for Continual Domain Generalization over Temporal Drift
Exploring Why Object Recognition Performance Degrades Across Income Levels and Geographies with Factor Annotations
Nearly Optimal VC-Dimension and Pseudo-Dimension Bounds for Deep Neural Network Derivatives
Automatic Grouping for Efficient Cooperative Multi-Agent Reinforcement Learning
Predicting the Risk of Complications in Coronary Artery Bypass Operations using Neural Networks
Speaker Comparison with Inner Product Discriminant Functions
Mesogeos: A multi-purpose dataset for data-driven wildfire modeling in the Mediterranean
Low-Rank Modular Reinforcement Learning via Muscle Synergy
Inducing Metric Violations in Human Similarity Judgements
Stochastic Optimal Control and Estimation with Multiplicative and Internal Noise
LVM-Med: Learning Large-Scale Self-Supervised Vision Models for Medical Imaging via Second-order Graph Matching
Contrastive Adapters for Foundation Model Group Robustness
On the Consistency of Quick Shift
Contextual Stochastic Block Models
Boosting with Multiple Sources
Development of Orientation and Ocular Dominance Columns in Infant Macaques
Thresholding Bandit with Optimal Aggregate Regret
Learning to Detect Natural Image Boundaries Using Brightness and Texture
A unified model of short-range and long-range motion perception
PIDForest: Anomaly Detection via Partial Identification
Robustness via Uncertainty-aware Cycle Consistency
Reinforced Continual Learning
CRAYM: Neural Field Optimization via Camera RAY Matching
Addressing Bias in Online Selection with Limited Budget of Comparisons
Eigenvalue Decay Implies Polynomial-Time Learnability for Neural Networks
Diverse Message Passing for Attribute with Heterophily
Sounding Bodies: Modeling 3D Spatial Sound of Humans Using Body Pose and Audio
u-HuBERT: Unified Mixed-Modal Speech Pretraining And Zero-Shot Transfer to Unlabeled Modality
On Memorization in Probabilistic Deep Generative Models
Exploiting Semantic Relations for Glass Surface Detection
Fuzzy Clustering with Similarity Queries
Tagger: Deep Unsupervised Perceptual Grouping
Soft Superpixel Neighborhood Attention
Information-Theoretic Safe Exploration with Gaussian Processes
Towards Next-Level Post-Training Quantization of Hyper-Scale Transformers
Marksman Backdoor: Backdoor Attacks with Arbitrary Target Class
BIVA: A Very Deep Hierarchy of Latent Variables for Generative Modeling
Understanding Contrastive Learning via Distributionally Robust Optimization
Direct Multi-view Multi-person 3D Pose Estimation
The Hateful Memes Challenge: Competition Report
Deeply Shared Filter Bases for Parameter-Efficient Convolutional Neural Networks
Adversarial Examples for k-Nearest Neighbor Classifiers Based on Higher-Order Voronoi Diagrams
Sample Efficient Reinforcement Learning through Learning from Demonstrations in Minecraft
Active Offline Policy Selection
Adversarial Training and Robustness for Multiple Perturbations
Noise-Contrastive Estimation for Multivariate Point Processes
A Combinatorial Perspective on the Optimization of Shallow ReLU Networks
Distributed Multi-Player Bandits - a Game of Thrones Approach
Causal Bandits: Learning Good Interventions via Causal Inference
Dopamine Modulation in a Basal Ganglio-cortical Network Implements Saliency-based Gating of Working Memory
Transfusion: Understanding Transfer Learning for Medical Imaging
Neural Approximation of Graph Topological Features
Linear Uncertainty Quantification of Graphical Model Inference
ProTransformer: Robustify Transformers via Plug-and-Play Paradigm
Optimization by Mean Field Annealing
Boosting Spectral Clustering on Incomplete Data via Kernel Correction and Affinity Learning
Combining Features for BCI
ID and OOD Performance Are Sometimes Inversely Correlated on Real-world Datasets
Generating Highly Designable Proteins with Geometric Algebra Flow Matching
Distributed Estimation with Multiple Samples per User: Sharp Rates and Phase Transition
QC-StyleGAN - Quality Controllable Image Generation and Manipulation
Heterogeneous Graph Learning for Visual Commonsense Reasoning
Multivariate Dyadic Regression Trees for Sparse Learning Problems
When Cyclic Coordinate Descent Outperforms Randomized Coordinate Descent
Beyond Value-Function Gaps: Improved Instance-Dependent Regret Bounds for Episodic Reinforcement Learning
Implicit Bias of Gradient Descent for Two-layer ReLU and Leaky ReLU Networks on Nearly-orthogonal Data
Improving Sparse Decomposition of Language Model Activations with Gated Sparse Autoencoders
GenRec: Unifying Video Generation and Recognition with Diffusion Models
Does Localization Inform Editing? Surprising Differences in Causality-Based Localization vs. Knowledge Editing in Language Models
Supported Value Regularization for Offline Reinforcement Learning
IRCAN: Mitigating Knowledge Conflicts in LLM Generation via Identifying and Reweighting Context-Aware Neurons
Discrete-Smoothness in Online Algorithms with Predictions
Supervised learning through the lens of compression
Instance-Dependent Near-Optimal Policy Identification in Linear MDPs via Online Experiment Design
Towards Scalable Unpaired Virtual Try-On via Patch-Routed Spatially-Adaptive GAN
An Efficient High-dimensional Gradient Estimator for Stochastic Differential Equations
Limits of Private Learning with Access to Public Data
Convergence of Large Margin Separable Linear Classification
The Equivalence of Dynamic and Strategic Stability under Regularized Learning in Games
Self-Adaptive Training: beyond Empirical Risk Minimization
Active Classification with Few Queries under Misspecification
Robustly overfitting latents for flexible neural image compression
Adaptive Graph Convolutional Recurrent Network for Traffic Forecasting
pfl-research: simulation framework for accelerating research in Private Federated Learning
The BigScience ROOTS Corpus: A 1.6TB Composite Multilingual Dataset
Augmentations in Hypergraph Contrastive Learning: Fabricated and Generative
Necessary and sufficient graphical conditions for optimal adjustment sets in causal graphical models with hidden variables
Topological Relational Learning on Graphs
ManiSkill: Generalizable Manipulation Skill Benchmark with Large-Scale Demonstrations
Implicit Bias in Deep Linear Classification: Initialization Scale vs Training Accuracy
Language-based Action Concept Spaces Improve Video Self-Supervised Learning
Scalable design of Error-Correcting Output Codes using Discrete Optimization with Graph Coloring
An Efficient Implementation of the Back-propagation Algorithm on the Connection Machine CM-2
Invariance Principle Meets Information Bottleneck for Out-of-Distribution Generalization
Trading Place for Space: Increasing Location Resolution Reduces Contextual Capacity in Hippocampal Codes
Effective Training of a Neural Network Character Classifier for Word Recognition
Phase-Space Learning
Learning to Break the Loop: Analyzing and Mitigating Repetitions for Neural Text Generation
Calibrating Reasoning in Language Models with Internal Consistency
Dense Keypoints via Multiview Supervision
COLD: Causal reasOning in cLosed Daily activities