yusuke1997/dblp-id-title huggingface dataset:
Improving Coherence and Consistency in Neural Sequence Models with Dual-System, Neuro-Symbolic Reasoning
Assessing the Quality of Learned Local Models
Universal Approximation of Input-Output Maps by Temporal Convolutional Nets
UltraEdit: Instruction-based Fine-Grained Image Editing at Scale
Small-Variance Asymptotics for Hidden Markov Models
ODE2VAE: Deep generative second order ODEs with Bayesian neural networks
Provable Training for Graph Contrastive Learning
Locating Changes in Highly Dependent Data with Unknown Number of Change Points
CycleNet: Enhancing Time Series Forecasting through Modeling Periodic Patterns
Adaptive Retina with Center-Surround Receptive Field
DAC-DETR: Divide the Attention Layers and Conquer
Interactive Parts Model: An Application to Recognition of On-line Cursive Script
DynaMITE-RL: A Dynamic Model for Improved Temporal Meta-Reinforcement Learning
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Characterizing emergent representations in a space of candidate learning rules for deep networks
Bounds on marginal probability distributions
Inferring Elapsed Time from Stochastic Neural Processes
Self-Supervised Generalisation with Meta Auxiliary Learning
ContiFormer: Continuous-Time Transformer for Irregular Time Series Modeling
LibMOON: A Gradient-based MultiObjective OptimizatioN Library in PyTorch
Which Space Partitioning Tree to Use for Search?
Low-rank lottery tickets: finding efficient low-rank neural networks via matrix differential equations
Learning Optimal Commitment to Overcome Insecurity
Strictly Batch Imitation Learning by Energy-based Distribution Matching
Unleashing the Power of Contrastive Self-Supervised Visual Models via Contrast-Regularized Fine-Tuning
Unscrambling disease progression at scale: fast inference of event permutations with optimal transport
Recycling Privileged Learning and Distribution Matching for Fairness
On the Sublinear Regret of GP-UCB
Bayesian Detection of Infrequent Differences in Sets of Time Series with Shared Structure
Active Nearest-Neighbor Learning in Metric Spaces
SLAPS: Self-Supervision Improves Structure Learning for Graph Neural Networks
Breaking Reversibility Accelerates Langevin Dynamics for Non-Convex Optimization
Adversarial Robustness through Local Linearization
Envy-Free Classification
Scaling Gaussian Processes with Derivative Information Using Variational Inference
Creating a Public Repository for Joining Private Data
Learning Data Manipulation for Augmentation and Weighting
Surface Reconstruction using Learned Shape Models
Efficient Kernel Machines Using the Improved Fast Gauss Transform
On the Theoretical Properties of Noise Correlation in Stochastic Optimization
Online Reciprocal Recommendation with Theoretical Performance Guarantees
Agent Planning with World Knowledge Model
Context-dependent upper-confidence bounds for directed exploration
An Approximate, Efficient LP Solver for LP Rounding
Active Learning For Identifying Function Threshold Boundaries
Approximating the Permanent with Deep Rejection Sampling
Bitstream-Corrupted Video Recovery: A Novel Benchmark Dataset and Method
Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, December 5-10, 2016, Barcelona, Spain
Multitask Boosting for Survival Analysis with Competing Risks
Neural Population Geometry Reveals the Role of Stochasticity in Robust Perception
Robust Parameter Estimation and Model Selection for Neural Network Regression
Neural Network Implementation of Admission Control
Multivariate f-divergence Estimation With Confidence
Heterogeneity-Guided Client Sampling: Towards Fast and Efficient Non-IID Federated Learning
A Likelihood-Free Inference Framework for Population Genetic Data using Exchangeable Neural Networks
Recurrent Neural Networks for Missing or Asynchronous Data
Testing Semantic Importance via Betting
PromptRestorer: A Prompting Image Restoration Method with Degradation Perception
Replicability in Reinforcement Learning
A single gradient step finds adversarial examples on random two-layers neural networks
A Kernel Test for Three-Variable Interactions
A Theoretical Analysis of Fine-tuning with Linear Teachers
Sketch-GNN: Scalable Graph Neural Networks with Sublinear Training Complexity
SPRING: Studying Papers and Reasoning to play Games
Improving Auto-Augment via Augmentation-Wise Weight Sharing
Fourier-enhanced Implicit Neural Fusion Network for Multispectral and Hyperspectral Image Fusion
Graph Robustness Benchmark: Benchmarking the Adversarial Robustness of Graph Machine Learning
Functionally Constrained Algorithm Solves Convex Simple Bilevel Problem
Improving robustness to corruptions with multiplicative weight perturbations
Dynamical mean-field theory for stochastic gradient descent in Gaussian mixture classification
Regularization Learning Networks: Deep Learning for Tabular Datasets
Clustering via LP-based Stabilities
Dynamically Masked Discriminator for GANs
Differential Privacy Has Disparate Impact on Model Accuracy
Federated Bayesian Optimization via Thompson Sampling
Drill-down: Interactive Retrieval of Complex Scenes using Natural Language Queries
The Price of Privacy for Low-rank Factorization
Contextual Squeeze-and-Excitation for Efficient Few-Shot Image Classification
Practical Bayesian Optimization of Machine Learning Algorithms
Network Diffusions via Neural Mean-Field Dynamics
Estimating Epistemic and Aleatoric Uncertainty with a Single Model
Hyperparameter and Kernel Learning for Graph Based Semi-Supervised Classification
Toward Efficient Robust Training against Union of $\ell_p$ Threat Models
Neural Active Learning with Performance Guarantees
Single Model Uncertainty Estimation via Stochastic Data Centering
Revisiting K-mer Profile for Effective and Scalable Genome Representation Learning
Diffusion with Forward Models: Solving Stochastic Inverse Problems Without Direct Supervision
Improve Agents without Retraining: Parallel Tree Search with Off-Policy Correction
Consistent Aggregation of Objectives with Diverse Time Preferences Requires Non-Markovian Rewards
Fusion of Similarity Data in Clustering
One Microphone Blind Dereverberation Based on Quasi-periodicity of Speech Signals
Calculating Optimistic Likelihoods Using (Geodesically) Convex Optimization
Learning Lateral Interactions for Feature Binding and Sensory Segmentation
A Neural Edge-Detection Model for Enhanced Auditory Sensitivity in Modulated Noise
An Error Detection and Correction Framework for Connectomics
RandAugment: Practical Automated Data Augmentation with a Reduced Search Space
Learning Reward Machines for Partially Observable Reinforcement Learning
Multiple-Instance Pruning For Learning Efficient Cascade Detectors
Parallel Feature Selection Inspired by Group Testing
Assignment of Multiplicative Mixtures in Natural Images
Contrastive-Equivariant Self-Supervised Learning Improves Alignment with Primate Visual Area IT
Bayesian Nonparametric Models on Decomposable Graphs
BulletTrain: Accelerating Robust Neural Network Training via Boundary Example Mining
The Devil and the Network
A Gaussian Process Model of Quasar Spectral Energy Distributions
Detecting Anomalous Event Sequences with Temporal Point Processes
Brain encoding models based on multimodal transformers can transfer across language and vision
SpecExec: Massively Parallel Speculative Decoding For Interactive LLM Inference on Consumer Devices
Hardness in Markov Decision Processes: Theory and Practice
Movement Penalized Bayesian Optimization with Application to Wind Energy Systems
Stabilizing the Optimization of Neural Signed Distance Functions and Finer Shape Representation
Structure estimation for discrete graphical models: Generalized covariance matrices and their inverses
Medical Concept Normalization by Encoding Target Knowledge
Large Margin Multi-Task Metric Learning
Proper Value Equivalence
High Precision Causal Model Evaluation with Conditional Randomization
Variational Inverse Control with Events: A General Framework for Data-Driven Reward Definition
On the Accuracy of Influence Functions for Measuring Group Effects
Hyperparameter Optimization Is Deceiving Us, and How to Stop It
Bridging the Divide: Reconsidering Softmax and Linear Attention
Coordinate Transformation Learning of Hand Position Feedback Controller by Using Change of Position Error Norm
Learning to Tokenize for Generative Retrieval
Value Function Approximation with Diffusion Wavelets and Laplacian Eigenfunctions
Learning Cue-Invariant Visual Responses
Stochastic Optimal Control for Collective Variable Free Sampling of Molecular Transition Paths
FedGame: A Game-Theoretic Defense against Backdoor Attacks in Federated Learning
Fast and Robust Least Squares Estimation in Corrupted Linear Models
On the Computational Efficiency of Training Neural Networks
Action Imitation in Common Action Space for Customized Action Image Synthesis
Can We Gain More from Orthogonality Regularizations in Training Deep Networks?
Copulas as High-Dimensional Generative Models: Vine Copula Autoencoders
Learning Stationary Time Series using Gaussian Processes with Nonparametric Kernels
Using Pairs of Data-Points to Define Splits for Decision Trees
Joint Sub-bands Learning with Clique Structures for Wavelet Domain Super-Resolution
Schema for Motor Control Utilizing a Network Model of the Cerebellum
Regularized Laplacian Estimation and Fast Eigenvector Approximation
Deep Joint Task Learning for Generic Object Extraction
Oscillatory Tracking of Continuous Attractor Neural Networks Account for Phase Precession and Procession of Hippocampal Place Cells
Pipeline Parallelism with Controllable Memory
Retrieval-Augmented Multiple Instance Learning
Context as Filtering
Pl@ntNet-300K: a plant image dataset with high label ambiguity and a long-tailed distribution
Rates of Convergence for Nearest Neighbor Classification
Rewriting History with Inverse RL: Hindsight Inference for Policy Improvement
Shallow vs. Deep Sum-Product Networks
Community Detection Guarantees using Embeddings Learned by Node2Vec
Single Loop Gaussian Homotopy Method for Non-convex Optimization
The Empirical Impact of Neural Parameter Symmetries, or Lack Thereof
Threshold Network Learning in the Presence of Equivalences
What's Left? Concept Grounding with Logic-Enhanced Foundation Models
On Decomposing the Proximal Map
Uncertainty, phase and oscillatory hippocampal recall
Hidden Markov Model of Cortical Synaptic Plasticity: Derivation of the Learning Rule
The Effect of Network Width on the Performance of Large-batch Training
Learning Large Neighborhood Search Policy for Integer Programming
Error Propagation for Approximate Policy and Value Iteration
On Multilabel Classification and Ranking with Partial Feedback
Efficient Inference in Phylogenetic InDel Trees
On the Computational Utility of Consciousness
Rational neural networks
Breaking Bad: A Dataset for Geometric Fracture and Reassembly
Learning in Higher-Order "Artificial Dendritic Trees"
PhoCoLens: Photorealistic and Consistent Reconstruction in Lensless Imaging
Subordinate class recognition using relational object models
Spectral Entry-wise Matrix Estimation for Low-Rank Reinforcement Learning
Scalarization for Multi-Task and Multi-Domain Learning at Scale
Scalable imputation of genetic data with a discrete fragmentation-coagulation process
Generative View Synthesis: From Single-view Semantics to Novel-view Images
Einsum Benchmark: Enabling the Development of Next-Generation Tensor Execution Engines
Submodular + Concave
Unified Sample-Optimal Property Estimation in Near-Linear Time
Precise characterization of the prior predictive distribution of deep ReLU networks
3D Focusing-and-Matching Network for Multi-Instance Point Cloud Registration
GEQ: Gaussian Kernel Inspired Equilibrium Models
Scalable Inference of Overlapping Communities
On Sample-Efficient Offline Reinforcement Learning: Data Diversity, Posterior Sampling and Beyond
Convolutional spike-triggered covariance analysis for neural subunit models
VIME: Variational Information Maximizing Exploration
An Equivalence Between Static and Dynamic Regret Minimization
LT-Defense: Searching-free Backdoor Defense via Exploiting the Long-tailed Effect
Detecting Humans via Their Pose
Extra-Newton: A First Approach to Noise-Adaptive Accelerated Second-Order Methods
Towards Co-designing Neural Network Function Approximators with In-SRAM Computing
A Convergence Proof for the Softassign Quadratic Assignment Algorithm
An Inductive Bias for Tabular Deep Learning
Bayesian Experimental Design of Magnetic Resonance Imaging Sequences
Density Propagation and Improved Bounds on the Partition Function
Rates of convergence for the cluster tree
A Constructive Learning Algorithm for Discriminant Tangent Models
Last iterate convergence of SGD for Least-Squares in the Interpolation regime
Cross-Scale Self-Supervised Blind Image Deblurring via Implicit Neural Representation
Adaptive Sequence Submodularity
Help, Anna! Visual Navigation with Natural Multimodal Assistance via Retrospective Curiosity-Encouraging Imitation Learning
Gaussian Process Bandit Optimisation with Multi-fidelity Evaluations
A Connectionist Symbol Manipulator that Discovers the Structure of Context-Free Languages
Prospective Explanations: An Interactive Mechanism for Model Understanding
Participatory Personalization in Classification
Nonlinear physically-based models for decoding motor-cortical population activity
Versatile Energy-Based Probabilistic Models for High Energy Physics
Exponential Separations in Symmetric Neural Networks
Meta Learning with Relational Information for Short Sequences
DropCompute: simple and more robust distributed synchronous training via compute variance reduction
Sequencer: Deep LSTM for Image Classification
An Online Method for A Class of Distributionally Robust Optimization with Non-convex Objectives
Online learning in MDPs with linear function approximation and bandit feedback
Better Full-Matrix Regret via Parameter-Free Online Learning
Automatic Variational Inference in Stan
Efficient and direct estimation of a neural subunit model for sensory coding
YASS: Yet Another Spike Sorter
Interval Estimation for Reinforcement-Learning Algorithms in Continuous-State Domains
Federated Learning with Manifold Regularization and Normalized Update Reaggregation
Predicting Organic Reaction Outcomes with Weisfeiler-Lehman Network
Fractional Belief Propagation
Improving the Training of Rectified Flows
Storing Covariance by the Associative Long-Term Potentation and Depression of Synaptic Strengths in the Hippocampus
Influence of graph construction on graph-based clustering measures
No Train No Gain: Revisiting Efficient Training Algorithms For Transformer-based Language Models
Deep Fractional Fourier Transform
Feature Dropout: Revisiting the Role of Augmentations in Contrastive Learning
Feature Densities Are Required for Computing Feature Correspondences
What Makes Objects Similar: A Unified Multi-Metric Learning Approach
Robust Multi-agent Counterfactual Prediction
Scalable trust-region method for deep reinforcement learning using Kronecker-factored approximation
Neural Embeddings Rank: Aligning 3D latent dynamics with movements
Semidefinite relaxations for certifying robustness to adversarial examples
Graph Matching via Multiplicative Update Algorithm
VideoGUI: A Benchmark for GUI Automation from Instructional Videos
Robust Conformal Prediction Using Privileged Information
Park: An Open Platform for Learning-Augmented Computer Systems
Neuronal Maps for Sensory-Motor Control in the Barn Owl
Neural Latents Benchmark '21: Evaluating latent variable models of neural population activity
WinoGAViL: Gamified Association Benchmark to Challenge Vision-and-Language Models
Adversarial Multiple Source Domain Adaptation
Oscillation Onset in Neural Delayed Feedback
Nearly Tight Bounds For Differentially Private Multiway Cut
Certifiably Robust Graph Contrastive Learning
A Scale Free Algorithm for Stochastic Bandits with Bounded Kurtosis
RDumb: A simple approach that questions our progress in continual test-time adaptation
Exposing Attention Glitches with Flip-Flop Language Modeling
Relative Margin Machines
Low-Rank Regression with Tensor Responses
Approximate Inference in Continuous Determinantal Processes
Flexible statistical inference for mechanistic models of neural dynamics
Exploration in Model-based Reinforcement Learning by Empirically Estimating Learning Progress
Modular Flows: Differential Molecular Generation
Generalized Laplacian Eigenmaps
Coresets for Clustering with Fairness Constraints
Speech Recognition using SVMs
Learning convex polytopes with margin
Streaming, Distributed Variational Inference for Bayesian Nonparametrics
Derivative-Free Policy Optimization for Linear Risk-Sensitive and Robust Control Design: Implicit Regularization and Sample Complexity
Scalable Distributional Robustness in a Class of Non-Convex Optimization with Guarantees
On model selection consistency of penalized M-estimators: a geometric theory
UUKG: Unified Urban Knowledge Graph Dataset for Urban Spatiotemporal Prediction
Motion Forecasting in Continuous Driving
LiteVAE: Lightweight and Efficient Variational Autoencoders for Latent Diffusion Models
Addressing Leakage in Concept Bottleneck Models
Pruning with generalization based weight saliencies: gamma-OBD, gamma-OBS
A Tale of Two Features: Stable Diffusion Complements DINO for Zero-Shot Semantic Correspondence
Continuous Time Particle Filtering for fMRI
SuperGLUE: A Stickier Benchmark for General-Purpose Language Understanding Systems
Cyclades: Conflict-free Asynchronous Machine Learning
Towards Generalization and Simplicity in Continuous Control
CoPur: Certifiably Robust Collaborative Inference via Feature Purification
Learning Model Bias
Passive attention in artificial neural networks predicts human visual selectivity
ParaFuzz: An Interpretability-Driven Technique for Detecting Poisoned Samples in NLP
Adaptive Submodular Maximization in Bandit Setting
Clustering with Non-adaptive Subset Queries
Temporal-Difference Learning Using Distributed Error Signals
Linear-Memory and Decomposition-Invariant Linearly Convergent Conditional Gradient Algorithm for Structured Polytopes
Assessing Blinding in Clinical Trials
Federated Graph Classification over Non-IID Graphs
Learning Options via Compression
Spectral Modification of Graphs for Improved Spectral Clustering
On Efficient Online Imitation Learning via Classification
Thinning Measurement Models and Questionnaire Design
Explaining the Uncertain: Stochastic Shapley Values for Gaussian Process Models
Reverse-engineering recurrent neural network solutions to a hierarchical inference task for mice
Stable Vectorization of Multiparameter Persistent Homology using Signed Barcodes as Measures
Perturbative M-Sequences for Auditory Systems Identification
Robust Model Selection and Nearly-Proper Learning for GMMs
Parallel Support Vector Machines: The Cascade SVM
Efficient Out-of-Sample Extension of Dominant-Set Clusters
Projection Robust Wasserstein Distance and Riemannian Optimization
Kernel Logistic Regression and the Import Vector Machine
Semantic Labeling of 3D Point Clouds for Indoor Scenes
Label Noise: Ignorance Is Bliss
Your Transformer May Not be as Powerful as You Expect
Cross-Validation Optimization for Large Scale Hierarchical Classification Kernel Methods
Tight Dimensionality Reduction for Sketching Low Degree Polynomial Kernels
Training Neural Networks with Deficient Data
Excluding the Irrelevant: Focusing Reinforcement Learning through Continuous Action Masking
Using Social Dynamics to Make Individual Predictions: Variational Inference with a Stochastic Kinetic Model
Non-parametric Regression Between Manifolds
Lifelong Domain Adaptation via Consolidated Internal Distribution
Antigen-Specific Antibody Design via Direct Energy-based Preference Optimization
One-shot Federated Learning via Synthetic Distiller-Distillate Communication
Efficient Algorithm for Privately Releasing Smooth Queries
Large Spatial Model: End-to-end Unposed Images to Semantic 3D
Unsupervised Regression with Applications to Nonlinear System Identification
Improved Convergence in High Probability of Clipped Gradient Methods with Heavy Tailed Noise
Combining Neural Network Regression Estimates with Regularized Linear Weights
Learning to Handle Complex Constraints for Vehicle Routing Problems
Structure-Preserving 3D Garment Modeling with Neural Sewing Machines
Bayesian Synchronous Grammar Induction
Root Cause Analysis of Failures in Microservices through Causal Discovery
Back Razor: Memory-Efficient Transfer Learning by Self-Sparsified Backpropagation
Neural Sampling in Hierarchical Exponential-family Energy-based Models
Bounds on the Complexity of Recurrent Neural Network Implementations of Finite State Machines
Learned Robust PCA: A Scalable Deep Unfolding Approach for High-Dimensional Outlier Detection
Neural Networks for Template Matching: Application to Real-Time Classification of the Action Potentials of Real Neurons
Conditional Random Sampling: A Sketch-based Sampling Technique for Sparse Data
Transformation Invariant Autoassociation with Application to Handwritten Character Recognition
Palm up: Playing in the Latent Manifold for Unsupervised Pretraining
Learning with Fredholm Kernels
DP-SSL: Towards Robust Semi-supervised Learning with A Few Labeled Samples
Stochastic Gradient Descent, Weighted Sampling, and the Randomized Kaczmarz algorithm
Meta Internal Learning
Learning List-Level Domain-Invariant Representations for Ranking
Deep Multi-State Dynamic Recurrent Neural Networks Operating on Wavelet Based Neural Features for Robust Brain Machine Interfaces
Factorized Contrastive Learning: Going Beyond Multi-view Redundancy
FedPop: A Bayesian Approach for Personalised Federated Learning
Scaling provable adversarial defenses
QuaRot: Outlier-Free 4-Bit Inference in Rotated LLMs
AVOIDDS: Aircraft Vision-based Intruder Detection Dataset and Simulator
Grouping Components of Three-Dimensional Moving Objects in Area MST of Visual Cortex
Extending Lagrangian and Hamiltonian Neural Networks with Differentiable Contact Models
The Ni1000: High Speed Parallel VLSI for Implementing Multilayer Perceptrons
Batch Renormalization: Towards Reducing Minibatch Dependence in Batch-Normalized Models
Versatile Multi-stage Graph Neural Network for Circuit Representation
Implicit Bias of Mirror Flow on Separable Data
Quantized Kernel Learning for Feature Matching
Using matrices to model symbolic relationship
How Robust are the Estimated Effects of Nonpharmaceutical Interventions against COVID-19?
Optimally Deceiving a Learning Leader in Stackelberg Games
Boosting with Abstention
SPD domain-specific batch normalization to crack interpretable unsupervised domain adaptation in EEG
Co-Modality Graph Contrastive Learning for Imbalanced Node Classification
Nonparametric sparse hierarchical models describe V1 fMRI responses to natural images
Deep Random Splines for Point Process Intensity Estimation of Neural Population Data
Non-Asymptotic Analysis of Stochastic Approximation Algorithms for Machine Learning
Objaverse-XL: A Universe of 10M+ 3D Objects
One Positive Label is Sufficient: Single-Positive Multi-Label Learning with Label Enhancement
On Regret with Multiple Best Arms
BadPrompt: Backdoor Attacks on Continuous Prompts
A Simple Unified Framework for Detecting Out-of-Distribution Samples and Adversarial Attacks
What Knowledge Gets Distilled in Knowledge Distillation?
Joint Attribute and Model Generalization Learning for Privacy-Preserving Action Recognition
Support Vector Machines Applied to Face Recognition
Discovering Viewpoint-Invariant Relationships That Characterize Objects
Language Models are Few-Shot Learners
Entrywise error bounds for low-rank approximations of kernel matrices
Linear Combinations of Optic Flow Vectors for Estimating Self-Motion - a Real-World Test of a Neural Model
Active Learning of Classifiers with Label and Seed Queries
ChronoMagic-Bench: A Benchmark for Metamorphic Evaluation of Text-to-Time-lapse Video Generation
MGDD: A Meta Generator for Fast Dataset Distillation
PerfectDou: Dominating DouDizhu with Perfect Information Distillation
Generalization Performance of Some Learning Problems in Hilbert Functional Spaces
An Analysis of Turbo Decoding with Gaussian Densities