yusuke1997/dblp-id-title huggingface dataset:
Towards Unsupervised Model Selection for Domain Adaptive Object Detection
Dynamic Analysis of Higher-Order Coordination in Neuronal Assemblies via De-Sparsified Orthogonal Matching Pursuit
Graph Clustering With Missing Data: Convex Algorithms and Analysis
PCA of high dimensional random walks with comparison to neural network training
Representation Learning via Consistent Assignment of Views over Random Partitions
Continuous Partitioning for Graph-Based Semi-Supervised Learning
Extreme bandits
Learning HMMs with Nonparametric Emissions via Spectral Decompositions of Continuous Matrices
Efficient Graph Matching for Correlated Stochastic Block Models
Scaling Properties of Coarse-Coded Symbol Memories
A general approximation lower bound in $L^p$ norm, with applications to feed-forward neural networks
Improving Topic Coherence with Regularized Topic Models
Online Bayesian Persuasion Without a Clue
Universal Function Approximation on Graphs
DisC-GS: Discontinuity-aware Gaussian Splatting
Learning Feature Sparse Principal Subspace
SageMix: Saliency-Guided Mixup for Point Clouds
Modular Meta-Learning with Shrinkage
How SGD Selects the Global Minima in Over-parameterized Learning: A Dynamical Stability Perspective
MinVIS: A Minimal Video Instance Segmentation Framework without Video-based Training
PerSim: Data-Efficient Offline Reinforcement Learning with Heterogeneous Agents via Personalized Simulators
Boosted Dyadic Kernel Discriminants
The Geometry of Deep Networks: Power Diagram Subdivision
Continuous-time edge modelling using non-parametric point processes
Adaptive Shrinkage Estimation for Streaming Graphs
A Model of Distributed Sensorimotor Control in the Cockroach Escape Turn
Fine-Grained Theoretical Analysis of Federated Zeroth-Order Optimization
Sliced Mutual Information: A Scalable Measure of Statistical Dependence
Make Continual Learning Stronger via C-Flat
Adversarially Robust Multi-task Representation Learning
Zeroth-Order Sampling Methods for Non-Log-Concave Distributions: Alleviating Metastability by Denoising Diffusion
Convex optimization based on global lower second-order models
Evaluation of Human-AI Teams for Learned and Rule-Based Agents in Hanabi
Distributed Low-rank Matrix Factorization With Exact Consensus
Incremental Local Gaussian Regression
Parsimonious Bayesian deep networks
Heavy-Tailed Process Priors for Selective Shrinkage
Exploration-Exploitation in Multi-Agent Competition: Convergence with Bounded Rationality
Proving Olympiad Algebraic Inequalities without Human Demonstrations
Neural Residual Diffusion Models for Deep Scalable Vision Generation
Is normalization indispensable for training deep neural network?
Single-Call Stochastic Extragradient Methods for Structured Non-monotone Variational Inequalities: Improved Analysis under Weaker Conditions
On two ways to use determinantal point processes for Monte Carlo integration
DiViNeT: 3D Reconstruction from Disparate Views using Neural Template Regularization
AttentionXML: Label Tree-based Attention-Aware Deep Model for High-Performance Extreme Multi-Label Text Classification
Mixed Dynamics In Linear Networks: Unifying the Lazy and Active Regimes
Bypassing spike sorting: Density-based decoding using spike localization from dense multielectrode probes
Sigsoftmax: Reanalysis of the Softmax Bottleneck
Hierarchical Skills for Efficient Exploration
An Efficient Dataset Condensation Plugin and Its Application to Continual Learning
Using Curvature Information for Fast Stochastic Search
QuPeD: Quantized Personalization via Distillation with Applications to Federated Learning
VideoLLM-MoD: Efficient Video-Language Streaming with Mixture-of-Depths Vision Computation
An Alternative Infinite Mixture Of Gaussian Process Experts
sEMG Gesture Recognition with a Simple Model of Attention
Multi-armed bandits on implicit metric spaces
Constraining Gaussian Processes to Systems of Linear Ordinary Differential Equations
DICES Dataset: Diversity in Conversational AI Evaluation for Safety
Quadratic Decomposable Submodular Function Minimization
Mapping a Manifold of Perceptual Observations
A Support Vector Method for Clustering
Calibrated Data-Dependent Constraints with Exact Satisfaction Guarantees
Robust and differentially private mean estimation
A Graphical Transformation for Belief Propagation: Maximum Weight Matchings and Odd-Sized Cycles
B-cosification: Transforming Deep Neural Networks to be Inherently Interpretable
Gaussian process modulated renewal processes
Robust Concept Erasure via Kernelized Rate-Distortion Maximization
Giving Feedback on Interactive Student Programs with Meta-Exploration
Diversify, Contextualize, and Adapt: Efficient Entropy Modeling for Neural Image Codec
RGFN: Synthesizable Molecular Generation Using GFlowNets
Large-Scale Matrix Factorization with Missing Data under Additional Constraints
Prompt Pre-Training with Twenty-Thousand Classes for Open-Vocabulary Visual Recognition
The ToMCAT Dataset
Offline RL with Discrete Proxy Representations for Generalizability in POMDPs
Predtron: A Family of Online Algorithms for General Prediction Problems
Simplifying Mixture Models through Function Approximation
Stochastic Halpern Iteration with Variance Reduction for Stochastic Monotone Inclusions
Delta-CoMe: Training-Free Delta-Compression with Mixed-Precision for Large Language Models
Provably Efficient Reinforcement Learning with Multinomial Logit Function Approximation
Learning Fairness in Multi-Agent Systems
Non-Asymptotic Gap-Dependent Regret Bounds for Tabular MDPs
Nonparametric Boundary Geometry in Physics Informed Deep Learning
Correlations strike back (again): the case of associative memory retrieval
DTs: Dynamic Trees
Human-Robotic Prosthesis as Collaborating Agents for Symmetrical Walking
Regularized Spectral Clustering under the Degree-Corrected Stochastic Blockmodel
Feature Selection in Mixture-Based Clustering
Discriminative Unsupervised Feature Learning with Convolutional Neural Networks
AUDIT: Audio Editing by Following Instructions with Latent Diffusion Models
Support vector machines and linear regression coincide with very high-dimensional features
Understanding Scaling Laws with Statistical and Approximation Theory for Transformer Neural Networks on Intrinsically Low-dimensional Data
Emergence of Shape Bias in Convolutional Neural Networks through Activation Sparsity
ReMAP: Neural Model Reprogramming with Network Inversion and Retrieval-Augmented Mapping for Adaptive Motion Forecasting
Gacs-Korner Common Information Variational Autoencoder
Near Optimal Exploration-Exploitation in Non-Communicating Markov Decision Processes
A New Approximate Maximal Margin Classification Algorithm
Pruning Random Forests for Prediction on a Budget
Optimal models of sound localization by barn owls
Mixability made efficient: Fast online multiclass logistic regression
Learning to Hash with Binary Reconstructive Embeddings
Safetywashing: Do AI Safety Benchmarks Actually Measure Safety Progress?
Do Convnets Learn Correspondence?
Fast Fourier Convolution
TinyLUT: Tiny Look-Up Table for Efficient Image Restoration at the Edge
Distributional Population Codes and Multiple Motion Models
CD-GraB: Coordinating Distributed Example Orders for Provably Accelerated Training
Understanding Bandits with Graph Feedback
Length Optimization in Conformal Prediction
DNN-based Topology Optimisation: Spatial Invariance and Neural Tangent Kernel
Credal Deep Ensembles for Uncertainty Quantification
Spatially Aggregated Gaussian Processes with Multivariate Areal Outputs
Rethinking the CSC Model for Natural Images
Sequence-to-Segment Networks for Segment Detection
Efficient Model for Image Classification With Regularization Tricks
Communication-Efficient Distributed Learning via Lazily Aggregated Quantized Gradients
Diverse Image Captioning with Context-Object Split Latent Spaces
Variational Inference over Combinatorial Spaces
New Adaptive Algorithms for Online Classification
Collaborative Video Diffusion: Consistent Multi-video Generation with Camera Control
Getting ViT in Shape: Scaling Laws for Compute-Optimal Model Design
Multi-Player Zero-Sum Markov Games with Networked Separable Interactions
The s-value: evaluating stability with respect to distributional shifts
Unleashing the Full Potential of Product Quantization for Large-Scale Image Retrieval
Simplifying Constraint Inference with Inverse Reinforcement Learning
Learning Versatile Skills with Curriculum Masking
Unifying Predictions of Deterministic and Stochastic Physics in Mesh-reduced Space with Sequential Flow Generative Model
Evidence Optimization Techniques for Estimating Stimulus-Response Functions
Semialgebraic Optimization for Lipschitz Constants of ReLU Networks
Stable Diffusion is Unstable
Projection-Free Methods for Stochastic Simple Bilevel Optimization with Convex Lower-level Problem
On student-teacher deviations in distillation: does it pay to disobey?
Meta Two-Sample Testing: Learning Kernels for Testing with Limited Data
No Free Delivery Service: Epistemic limits of passive data collection in complex social systems
Scattering GCN: Overcoming Oversmoothness in Graph Convolutional Networks
McRank: Learning to Rank Using Multiple Classification and Gradient Boosting
Generalization Bounds of Stochastic Gradient Descent for Wide and Deep Neural Networks
PlanGAN: Model-based Planning With Sparse Rewards and Multiple Goals
Enhancing User Intent Capture in Session-Based Recommendation with Attribute Patterns
Bandits with Abstention under Expert Advice
Double or Nothing: Multiplicative Incentive Mechanisms for Crowdsourcing
Estimating the Unseen: Improved Estimators for Entropy and other Properties
ALCOVE: A Connectionist Model of Human Category Learning
A Characterization of Semi-Supervised Adversarially Robust PAC Learnability
Provably Strict Generalisation Benefit for Invariance in Kernel Methods
Greedy inference with structure-exploiting lazy maps
CV-VAE: A Compatible Video VAE for Latent Generative Video Models
Learning to Agglomerate Superpixel Hierarchies
SerialRank: Spectral Ranking using Seriation
SpatialRGPT: Grounded Spatial Reasoning in Vision-Language Models
Is Your HD Map Constructor Reliable under Sensor Corruptions?
Seeing the Image: Prioritizing Visual Correlation by Contrastive Alignment
Autoregressive Policy Optimization for Constrained Allocation Tasks
Amazon-M2: A Multilingual Multi-locale Shopping Session Dataset for Recommendation and Text Generation
Subgraph Detection Using Eigenvector L1 Norms
Bayesian Optimization with High-Dimensional Outputs
SR-CACO-2: A Dataset for Confocal Fluorescence Microscopy Image Super-Resolution
Can Transformers Smell Like Humans?
Stationarity of Synaptic Coupling Strength Between Neurons with Nonstationary Discharge Properties
Hierarchical Clustering via Spreading Metrics
Private Identity Testing for High-Dimensional Distributions
General Cutting Planes for Bound-Propagation-Based Neural Network Verification
Near-minimax recursive density estimation on the binary hypercube
Pre-trained Adversarial Perturbations
Training Subset Selection for Weak Supervision
XDO: A Double Oracle Algorithm for Extensive-Form Games
Michelangelo: Conditional 3D Shape Generation based on Shape-Image-Text Aligned Latent Representation
No-Press Diplomacy from Scratch
Stochastic Collapse: How Gradient Noise Attracts SGD Dynamics Towards Simpler Subnetworks
Actor-Critic Policy Optimization in Partially Observable Multiagent Environments
Cyclizing Clusters via Zeta Function of a Graph
Online Adaptation to Label Distribution Shift
Online PCA for Contaminated Data
Inconsistency, Instability, and Generalization Gap of Deep Neural Network Training
Bridge the Modality and Capability Gaps in Vision-Language Model Selection
The Point Where Reality Meets Fantasy: Mixed Adversarial Generators for Image Splice Detection
Efficient Activation Function Optimization through Surrogate Modeling
Optimal Rates for Random Order Online Optimization
Winner-Take-All Networks of O(N) Complexity
Optimal Epoch Stochastic Gradient Descent Ascent Methods for Min-Max Optimization
Learning sparse dynamic linear systems using stable spline kernels and exponential hyperpriors
Canonical 3D Deformer Maps: Unifying parametric and non-parametric methods for dense weakly-supervised category reconstruction
Stealth edits to large language models
Discriminative Gaifman Models
What Uncertainties Do We Need in Bayesian Deep Learning for Computer Vision?
A Theory of Decision Making Under Dynamic Context
Learning-Augmented Algorithms for the Bahncard Problem
Electronic Receptors for Tactile/Haptic Sensing
On the Role of Entanglement and Statistics in Learning
Sampling from a k-DPP without looking at all items
GAGA: Deciphering Age-path of Generalized Self-paced Regularizer
Online Learning: Stochastic, Constrained, and Smoothed Adversaries
Ambiguous Model Learning Made Unambiguous with 1/f Priors
Expressive Power and Approximation Errors of Restricted Boltzmann Machines
Why Do Artificially Generated Data Help Adversarial Robustness
REBORN: Reinforcement-Learned Boundary Segmentation with Iterative Training for Unsupervised ASR
QPyTorch: A Low-Precision Arithmetic Simulation Framework
Face Recognition Using Kernel Methods
Jump Self-attention: Capturing High-order Statistics in Transformers
The Power of Optimization from Samples
MURPHY: A Robot that Learns by Doing
A Non-asymptotic Analysis of Non-parametric Temporal-Difference Learning
TANKBind: Trigonometry-Aware Neural NetworKs for Drug-Protein Binding Structure Prediction
Automated scalable segmentation of neurons from multispectral images
MVDiffusion: Enabling Holistic Multi-view Image Generation with Correspondence-Aware Diffusion
Nonbacktracking Bounds on the Influence in Independent Cascade Models
Glyce: Glyph-vectors for Chinese Character Representations
Accelerating Matroid Optimization through Fast Imprecise Oracles
The Benefits of Implicit Regularization from SGD in Least Squares Problems
Symplectic Spectrum Gaussian Processes: Learning Hamiltonians from Noisy and Sparse Data
Split LBI: An Iterative Regularization Path with Structural Sparsity
The Transient Nature of Emergent In-Context Learning in Transformers
High-dimensional support union recovery in multivariate regression
Unveiling the Hidden Structure of Self-Attention via Kernel Principal Component Analysis
Graph Meta Learning via Local Subgraphs
Neuronal Competition Groups with Supervised STDP for Spike-Based Classification
Disentangled Style Domain for Implicit z-Watermark Towards Copyright Protection
Descent Steps of a Relation-Aware Energy Produce Heterogeneous Graph Neural Networks
Source Separation with a Sensor Array Using Graphical Models and Subband Filtering
Learning-to-Cache: Accelerating Diffusion Transformer via Layer Caching
Quasi-Newton Methods for Saddle Point Problems
Probabilistic Inference in Reinforcement Learning Done Right
Diffusion-based Reinforcement Learning via Q-weighted Variational Policy Optimization
Neural Human Performer: Learning Generalizable Radiance Fields for Human Performance Rendering
The Infinite Gamma-Poisson Feature Model
Predicting Deep Neural Network Generalization with Perturbation Response Curves
Equivariant Machine Learning on Graphs with Nonlinear Spectral Filters
COVID-19 Sounds: A Large-Scale Audio Dataset for Digital Respiratory Screening
Double Machine Learning Density Estimation for Local Treatment Effects with Instruments
Read-ME: Refactorizing LLMs as Router-Decoupled Mixture of Experts with System Co-Design
Group Robust Classification Without Any Group Information
Improved Guarantees for Offline Stochastic Matching via new Ordered Contention Resolution Schemes
Differentiable Learning of Submodular Functions
Oracle-Efficient Reinforcement Learning for Max Value Ensembles
Learning Representations by Recirculation
HC-GAE: The Hierarchical Cluster-based Graph Auto-Encoder for Graph Representation Learning
On the Suboptimality of Thompson Sampling in High Dimensions
Improving Multi-Task Generalization via Regularizing Spurious Correlation
Two Iterative Algorithms for Computing the Singular Value Decomposition from Input/Output Samples
Tree-Sliced Variants of Wasserstein Distances
Adapting to Unknown Low-Dimensional Structures in Score-Based Diffusion Models
A POMDP Extension with Belief-dependent Rewards
CoSE: Compositional Stroke Embeddings
Deep Coding Network
D 2 CSG: Unsupervised Learning of Compact CSG Trees with Dual Complements and Dropouts
Stability and Generalization for Markov Chain Stochastic Gradient Methods
Generalization error bounds for classifiers trained with interdependent data
ACIL: Analytic Class-Incremental Learning with Absolute Memorization and Privacy Protection
Byzantine Robustness and Partial Participation Can Be Achieved at Once: Just Clip Gradient Differences
Causal Regularization
GraphDE: A Generative Framework for Debiased Learning and Out-of-Distribution Detection on Graphs
Dual Space Gradient Descent for Online Learning
The geometry of hidden representations of large transformer models
Nonlinear random matrix theory for deep learning
Multilabel Classification by Hierarchical Partitioning and Data-dependent Grouping
Explaining Preferences with Shapley Values
Faster Relative Entropy Coding with Greedy Rejection Coding
Reshuffling Resampling Splits Can Improve Generalization of Hyperparameter Optimization
Reinforcement Learning for Dynamic Channel Allocation in Cellular Telephone Systems
Modeling Human Visual Motion Processing with Trainable Motion Energy Sensing and a Self-attention Network
Speculative Monte-Carlo Tree Search
PUZZLES: A Benchmark for Neural Algorithmic Reasoning
A Simple Language Model for Task-Oriented Dialogue
Dynamic Regret of Policy Optimization in Non-Stationary Environments
Why The Brain Separates Face Recognition From Object Recognition
TransAgent: Transfer Vision-Language Foundation Models with Heterogeneous Agent Collaboration
Convergence Rates of Active Learning for Maximum Likelihood Estimation
Understanding the Latent Space of Diffusion Models through the Lens of Riemannian Geometry
Radial Basis Functions: A Bayesian Treatment
Fairness and Efficiency in Online Class Matching
One-Line-of-Code Data Mollification Improves Optimization of Likelihood-based Generative Models
Efficient Simulation of Biological Neural Networks on Massively Parallel Supercomputers with Hypercube Architecture
Back Propagation is Sensitive to Initial Conditions
Rate-Distortion Theoretic Bounds on Generalization Error for Distributed Learning
Global Belief Recursive Neural Networks
Oracle-Efficient Regret Minimization in Factored MDPs with Unknown Structure
A Minimax Approach to Supervised Learning
Diffusion4D: Fast Spatial-temporal Consistent 4D generation via Video Diffusion Models
Hyperalignment of Multi-subject fMRI Data by Synchronized Projections
On the Scalability of Certified Adversarial Robustness with Generated Data
Label Efficient Learning of Transferable Representations acrosss Domains and Tasks
A Log-Domain Implementation of the Diffusion Network in Very Large Scale Integration
DiffNorm: Self-Supervised Normalization for Non-autoregressive Speech-to-speech Translation
Quantile Constrained Reinforcement Learning: A Reinforcement Learning Framework Constraining Outage Probability
Neural Diffusion Distance for Image Segmentation
The Information-Form Data Association Filter
The Ordered Residual Kernel for Robust Motion Subspace Clustering
ESSEN: Improving Evolution State Estimation for Temporal Networks using Von Neumann Entropy
Rescuing neural spike train models from bad MLE
LESS: Label-Efficient and Single-Stage Referring 3D Segmentation
The Performance of Convex Set Projection Based Neural Networks
Parameter Learning for Log-supermodular Distributions
A PAC-Bayes approach to the Set Covering Machine
Fast and Accurate k-means For Large Datasets
CorticalFlow: A Diffeomorphic Mesh Transformer Network for Cortical Surface Reconstruction
Fast Similarity Search via Optimal Sparse Lifting
Quantitative Propagation of Chaos for SGD in Wide Neural Networks
Constrained Latent Action Policies for Model-Based Offline Reinforcement Learning
Scalable Inference for Logistic-Normal Topic Models
Distributed Stochastic Optimization via Adaptive SGD
Whole Brain Vessel Graphs: A Dataset and Benchmark for Graph Learning and Neuroscience
Finite Sample Prediction and Recovery Bounds for Ordinal Embedding
Thunder: a Fast Coordinate Selection Solver for Sparse Learning
Accurate Layerwise Interpretable Competence Estimation
Möbius Transformation for Fast Inner Product Search on Graph
A Theoretical Understanding of Self-Correction through In-context Alignment
Kernel-Based Function Approximation for Average Reward Reinforcement Learning: An Optimist No-Regret Algorithm
Quantifying Statistical Significance of Neural Network-based Image Segmentation by Selective Inference
Distributed k-Clustering for Data with Heavy Noise
Two-sided fairness in rankings via Lorenz dominance
Contextual Pricing for Lipschitz Buyers
Minimax Regret for Stochastic Shortest Path
NeurIPS 2020 Competition and Demonstration Track: Revised selected papers
One-unit Learning Rules for Independent Component Analysis
Bayesian GAN
Independence clustering (without a matrix)
Teach Me to Explain: A Review of Datasets for Explainable Natural Language Processing
Timely Object Recognition
Mercury: A Code Efficiency Benchmark for Code Large Language Models
Learning a Single Neuron with Bias Using Gradient Descent
Spec-Gaussian: Anisotropic View-Dependent Appearance for 3D Gaussian Splatting
PLIP: Language-Image Pre-training for Person Representation Learning
GPyTorch: Blackbox Matrix-Matrix Gaussian Process Inference with GPU Acceleration
The Randomized Dependence Coefficient
MGF: Mixed Gaussian Flow for Diverse Trajectory Prediction
Fast Trainable Projection for Robust Fine-tuning
Extrapolative Continuous-time Bayesian Neural Network for Fast Training-free Test-time Adaptation
Variational Gaussian Process Dynamical Systems
Landscape analysis of an improved power method for tensor decomposition
NEON2: Finding Local Minima via First-Order Oracles
Advances in Neural Information Processing Systems 19, Proceedings of the Twentieth Annual Conference on Neural Information Processing Systems, Vancouver, British Columbia, Canada, December 4-7, 2006
Learning a Condensed Frame for Memory-Efficient Video Class-Incremental Learning
Using Hippocampal 'Plane Cells' for Navigation, Exploiting Phase Coding
A Greedy Approach for Budgeted Maximum Inner Product Search
Linearly Converging Error Compensated SGD
Near-Optimal Edge Evaluation in Explicit Generalized Binomial Graphs
On the Power of Small-size Graph Neural Networks for Linear Programming
OctreeOcc: Efficient and Multi-Granularity Occupancy Prediction Using Octree Queries
Modeling Shared responses in Neuroimaging Studies through MultiView ICA
Many-body Approximation for Non-negative Tensors
PROSPECT PTMs: Rich Labeled Tandem Mass Spectrometry Dataset of Modified Peptides for Machine Learning in Proteomics
DATA: Differentiable ArchiTecture Approximation
Detection of First and Second Order Motion
Missing Not at Random in Matrix Completion: The Effectiveness of Estimating Missingness Probabilities Under a Low Nuclear Norm Assumption
Online Learning with an Unknown Fairness Metric
Semi-Supervised Generative Models for Multiagent Trajectories
Associative Memories via Predictive Coding
Finding Optimal Tangent Points for Reducing Distortions of Hard-label Attacks
Localizing Memorization in SSL Vision Encoders
Catastrophic Data Leakage in Vertical Federated Learning
LAION-5B: An open large-scale dataset for training next generation image-text models
START: A Generalized State Space Model with Saliency-Driven Token-Aware Transformation
Margin-Independent Online Multiclass Learning via Convex Geometry
Off-Policy Risk Assessment in Contextual Bandits
Contrast Adaptation in Simple Cells by Changing the Transmitter Release Probability
Unifying Framework for Fast Learning Rate of Non-Sparse Multiple Kernel Learning
Training Image Estimators without Image Ground Truth
MoVA: Adapting Mixture of Vision Experts to Multimodal Context
On the Loss Landscape of Adversarial Training: Identifying Challenges and How to Overcome Them
Tools for Verifying Neural Models' Training Data
Self-Educated Language Agent with Hindsight Experience Replay for Instruction Following