yusuke1997/dblp-id-title huggingface dataset:
Moderate-fitting as a Natural Backdoor Defender for Pre-trained Language Models
RealTime QA: What's the Answer Right Now?
How fast to work: Response vigor, motivation and tonic dopamine
Foundations of Symbolic Languages for Model Interpretability
LinNet: Linear Network for Efficient Point Cloud Representation Learning
Penalized Principal Component Regression on Graphs for Analysis of Subnetworks
COCO-LM: Correcting and Contrasting Text Sequences for Language Model Pretraining
Efficient Algorithms for Learning Depth-2 Neural Networks with General ReLU Activations
Near-optimal learning with average Hölder smoothness
Asymptotics of smoothed Wasserstein distances in the small noise regime
No-Regret Algorithms for Unconstrained Online Convex Optimization
Stage-wise Training: An Improved Feature Learning Strategy for Deep Models
Coreset for Line-Sets Clustering
RaLEs: a Benchmark for Radiology Language Evaluations
Encoding Labeled Graphs by Labeling RAAM
Topkapi: Parallel and Fast Sketches for Finding Top-K Frequent Elements
Computational Guarantees for Doubly Entropic Wasserstein Barycenters
VB-LoRA: Extreme Parameter Efficient Fine-Tuning with Vector Banks
Rethinking the Value of Labels for Improving Class-Imbalanced Learning
PerspectiveNet: A Scene-consistent Image Generator for New View Synthesis in Real Indoor Environments
Region Mutual Information Loss for Semantic Segmentation
Addressing Spectral Bias of Deep Neural Networks by Multi-Grade Deep Learning
Investigating how ReLU-networks encode symmetries
Explainable Voting
Visualizing and Measuring the Geometry of BERT
Parameter Efficient Adaptation for Image Restoration with Heterogeneous Mixture-of-Experts
Speaking Your Language: Spatial Relationships in Interpretable Emergent Communication
Individual Arbitrariness and Group Fairness
Benchmarking the Robustness of Spatial-Temporal Models Against Corruptions
Few-Cost Salient Object Detection with Adversarial-Paced Learning
Multiview Aggregation for Learning Category-Specific Shape Reconstruction
Spherical Units as Dynamic Consequential Regions
Towards modular and programmable architecture search
Large Stepsize Gradient Descent for Non-Homogeneous Two-Layer Networks: Margin Improvement and Fast Optimization
On-the-Job Learning with Bayesian Decision Theory
Provably Faster Algorithms for Bilevel Optimization
Computation of Heading Direction from Optic Flow in Visual Cortex
Learning from Complementary Labels
Learning Distributed Representations for Structured Output Prediction
Augmented-SVM: Automatic space partitioning for combining multiple non-linear dynamics
Hybrid-MST: A Hybrid Active Sampling Strategy for Pairwise Preference Aggregation
AbdomenAtlas-8K: Annotating 8, 000 CT Volumes for Multi-Organ Segmentation in Three Weeks
TADAM: Task dependent adaptive metric for improved few-shot learning
Beyond Alternating Updates for Matrix Factorization with Inertial Bregman Proximal Gradient Algorithms
D-CIPHER: Discovery of Closed-form Partial Differential Equations
R 2 -Gaussian: Rectifying Radiative Gaussian Splatting for Tomographic Reconstruction
A Dataset for Efforts Towards Achieving the Sustainable Development Goal of Safe Working Environments
Flowification: Everything is a normalizing flow
Simulating a Primary Visual Cortex at the Front of CNNs Improves Robustness to Image Perturbations
FairVFL: A Fair Vertical Federated Learning Framework with Contrastive Adversarial Learning
Unified Guidance for Geometry-Conditioned Molecular Generation
RoboHive: A Unified Framework for Robot Learning
An Alternative to Variance: Gini Deviation for Risk-averse Policy Gradient
Disentangling Cognitive Diagnosis with Limited Exercise Labels
Structural Risk Minimization for Character Recognition
Auto Learning Attention
Generalization Error Bounds for Two-stage Recommender Systems with Tree Structure
Boosting Algorithms as Gradient Descent
MInference 1.0: Accelerating Pre-filling for Long-Context LLMs via Dynamic Sparse Attention
Continual Learning with Evolving Class Ontologies
MomentDiff: Generative Video Moment Retrieval from Random to Real
Learning on the Edge: Online Learning with Stochastic Feedback Graphs
Learning in Rational Agents
What Matters for Adversarial Imitation Learning?
Perturb-and-max-product: Sampling and learning in discrete energy-based models
Improving Generative Adversarial Networks via Adversarial Learning in Latent Space
argmax centroid
CCNLab: A Benchmarking Framework for Computational Cognitive Neuroscience
GAL: Gradient Assisted Learning for Decentralized Multi-Organization Collaborations
Choice Bandits
Rescaling, thinning or complementing? On goodness-of-fit procedures for point process models and Generalized Linear Models
Collaborative Learning via Prediction Consensus
Fast Resampling Weighted v-Statistics
Learning to Taste: A Multimodal Wine Dataset
Walsh-Hadamard Variational Inference for Bayesian Deep Learning
Learning Bounds for Greedy Approximation with Explicit Feature Maps from Multiple Kernels
Connecting Certified and Adversarial Training
Self-playing Adversarial Language Game Enhances LLM Reasoning
Optimistic Rates for Multi-Task Representation Learning
Non-Ergodic Alternating Proximal Augmented Lagrangian Algorithms with Optimal Rates
Temporal Sentence Grounding with Relevance Feedback in Videos
Adder Attention for Vision Transformer
Sequential Monte Carlo for Graphical Models
Why Warmup the Learning Rate? Underlying Mechanisms and Improvements
Learning the Structure of Similarity
VLSI Model of Primate Visual Smooth Pursuit
One-shot learning and big data with n=2
Insights into Pre-training via Simpler Synthetic Tasks
MKOR: Momentum-Enabled Kronecker-Factor-Based Optimizer Using Rank-1 Updates
A Unified Analysis of Federated Learning with Arbitrary Client Participation
Online Classification with Specificity Constraints
Cluster and Aggregate: Face Recognition with Large Probe Set
Analysis of Sensing Spectral for Signal Recovery under a Generalized Linear Model
On Riemannian Optimization over Positive Definite Matrices with the Bures-Wasserstein Geometry
Discriminative Metric Learning by Neighborhood Gerrymandering
Lightweight Vision Transformer with Bidirectional Interaction
Robust-Adaptive Control of Linear Systems: beyond Quadratic Costs
Learning Compositional Neural Programs with Recursive Tree Search and Planning
Generalization Error Bounds for Collaborative Prediction with Low-Rank Matrices
Towards a Zero-One Law for Column Subset Selection
Learning Robust Global Representations by Penalizing Local Predictive Power
Customizable Image Synthesis with Multiple Subjects
Sanity-Checking Pruning Methods: Random Tickets can Win the Jackpot
Decision Trees with Short Explainable Rules
Applications of Multi-Resolution Neural Networks to Mammography
Persuading Farsighted Receivers in MDPs: the Power of Honesty
Learning Transferable Graph Exploration
Dissect Black Box: Interpreting for Rule-Based Explanations in Unsupervised Anomaly Detection
Bridging OOD Detection and Generalization: A Graph-Theoretic View
Convergence of Cubic Regularization for Nonconvex Optimization under KL Property
Provable Editing of Deep Neural Networks using Parametric Linear Relaxation
Experimental Evaluation of Learning in a Neural Microsystem
Uncertainty-Based Offline Reinforcement Learning with Diversified Q-Ensemble
Modeling the Machine Learning Multiverse
Information-Theoretic Confidence Bounds for Reinforcement Learning
Learning Mutational Semantics
Accelerated Training for Matrix-norm Regularization: A Boosting Approach
Structure-Aware Image Segmentation with Homotopy Warping
Automatic Feature Induction for Stagewise Collaborative Filtering
(Almost) Provable Error Bounds Under Distribution Shift via Disagreement Discrepancy
Instruction-Guided Visual Masking
Constructing Distributed Representations Using Additive Clustering
Shaping the State Space Landscape in Recurrent Networks
Efficiently Learning One Hidden Layer ReLU Networks From Queries
On the Minimax Regret for Online Learning with Feedback Graphs
ResAD: A Simple Framework for Class Generalizable Anomaly Detection
Efficient Combinatorial Optimization via Heat Diffusion
Reflection Separation using a Pair of Unpolarized and Polarized Images
SSH (Sketch, Shingle, & Hash) for Indexing Massive-Scale Time Series
Wasserstein Logistic Regression with Mixed Features
GPPS: A Gaussian Process Positioning System for Cellular Networks
Personalized Online Federated Learning with Multiple Kernels
Network Model of State-Dependent Sequencing
Resolving Motion Ambiguities
An Information Theoretic Framework for Eukaryotic Gradient Sensing
Stateful Posted Pricing with Vanishing Regret via Dynamic Deterministic Markov Decision Processes
Taming Discrete Integration via the Boon of Dimensionality
PrivCirNet: Efficient Private Inference via Block Circulant Transformation
History Aware Multimodal Transformer for Vision-and-Language Navigation
Predictive Information Accelerates Learning in RL
Solving Graph-based Public Goods Games with Tree Search and Imitation Learning
Emergence of conjunctive visual features by quadratic independent component analysis
Fast Rates for Exp-concave Empirical Risk Minimization
On Margins and Generalisation for Voting Classifiers
Beyond Accuracy: Ensuring Correct Predictions With Correct Rationales
p-Poisson surface reconstruction in curl-free flow from point clouds
Manifold denoising by Nonlinear Robust Principal Component Analysis
How Much Restricted Isometry is Needed In Nonconvex Matrix Recovery?
A Novel Kernel for Learning a Neuron Model from Spike Train Data
Graph Neural Networks Need Cluster-Normalize-Activate Modules
Data-Centric Learning from Unlabeled Graphs with Diffusion Model
Mixtures of Gaussian Processes
Kernel Multimodal Continuous Attention
Bridging the Gap: Unifying the Training and Evaluation of Neural Network Binary Classifiers
Reading a Neural Code
Learning Substructure Invariance for Out-of-Distribution Molecular Representations
Stochastic Approximation Approaches to Group Distributionally Robust Optimization
What Size Net Gives Valid Generalization?
Penguin: Parallel-Packed Homomorphic Encryption for Fast Graph Convolutional Network Inference
Generalised Implicit Neural Representations
Optimizing Prompts for Text-to-Image Generation
iLSTD: Eligibility Traces and Convergence Analysis
Hierarchical Granularity Transfer Learning
HRFormer: High-Resolution Vision Transformer for Dense Predict
Differentiable Optimization of Generalized Nondecomposable Functions using Linear Programs
Tight Bounds for Collaborative PAC Learning via Multiplicative Weights
Minimax Optimal Algorithms for Unconstrained Linear Optimization
Scalable Kernel Inverse Optimization
Vision Transformer Neural Architecture Search for Out-of-Distribution Generalization: Benchmark and Insights
Kernel Instrumental Variable Regression
Deepcode: Feedback Codes via Deep Learning
Privacy Assessment on Reconstructed Images: Are Existing Evaluation Metrics Faithful to Human Perception?
GREATS: Online Selection of High-Quality Data for LLM Training in Every Iteration
Gradient-EM Bayesian Meta-Learning
Adversarial Robustness is at Odds with Lazy Training
Fast and Memory Efficient Differentially Private-SGD via JL Projections
Extracting Training Data from Molecular Pre-trained Models
PixelGAN Autoencoders
Efficient Non-greedy Optimization of Decision Trees
Dual-Curriculum Contrastive Multi-Instance Learning for Cancer Prognosis Analysis with Whole Slide Images
Automatically Learning Hybrid Digital Twins of Dynamical Systems
How does Weight Correlation Affect Generalisation Ability of Deep Neural Networks?
Parameter-Inverted Image Pyramid Networks
StackEval: Benchmarking LLMs in Coding Assistance
Learning on graphs using Orthonormal Representation is Statistically Consistent
FMMformer: Efficient and Flexible Transformer via Decomposed Near-field and Far-field Attention
Multipole Graph Neural Operator for Parametric Partial Differential Equations
Kernelized Heterogeneous Risk Minimization
Finding Regions of Heterogeneity in Decision-Making via Expected Conditional Covariance
Graphons, mergeons, and so on!
Adaptive Multi-Task Lasso: with Application to eQTL Detection
Margin-Based Few-Shot Class-Incremental Learning with Class-Level Overfitting Mitigation
Unsupervised Meta-Learning for Few-Shot Image Classification
Efficient Output Kernel Learning for Multiple Tasks
Modelling the Dynamics of Multiagent Q-Learning in Repeated Symmetric Games: a Mean Field Theoretic Approach
Annealing between distributions by averaging moments
Greedy Hash: Towards Fast Optimization for Accurate Hash Coding in CNN
The Decision List Machine
Interactive Grounded Language Understanding in a Collaborative Environment: IGLU 2021
The Limits of Post-Selection Generalization
Learning the Geometry of Wave-Based Imaging
Kernel Latent SVM for Visual Recognition
Combinatorial Optimization for Panoptic Segmentation: A Fully Differentiable Approach
Fast Asymptotically Optimal Algorithms for Non-Parametric Stochastic Bandits
Neural Stochastic PDEs: Resolution-Invariant Learning of Continuous Spatiotemporal Dynamics
Statistical Consistency of Top-k Ranking
Deep Combinatorial Aggregation
Optimal and Adaptive Monteiro-Svaiter Acceleration
Machine Teaching of Active Sequential Learners
A Path to Simpler Models Starts With Noise
Smooth Fictitious Play in Stochastic Games with Perturbed Payoffs and Unknown Transitions
The Poisson Gamma Belief Network
On Human-Aligned Risk Minimization
Approximate Value Equivalence
Probing Classifiers are Unreliable for Concept Removal and Detection
Adaptive On-line Learning in Changing Environments
FourierFormer: Transformer Meets Generalized Fourier Integral Theorem
Simple steps are all you need: Frank-Wolfe and generalized self-concordant functions
AHA: Human-Assisted Out-of-Distribution Generalization and Detection
Towards Understanding the Condensation of Neural Networks at Initial Training
Nash Equilibria of Static Prediction Games
Historical Test-time Prompt Tuning for Vision Foundation Models
On Tropistic Processing and Its Applications
Off-Policy Evaluation for Action-Dependent Non-stationary Environments
A Probabilistic Approach for Optimizing Spectral Clustering
PriorBand: Practical Hyperparameter Optimization in the Age of Deep Learning
Redundancy-Free Message Passing for Graph Neural Networks
Unsupervised Sequence Classification using Sequential Output Statistics
CARES: A Comprehensive Benchmark of Trustworthiness in Medical Vision Language Models
Distribution Aligning Refinery of Pseudo-label for Imbalanced Semi-supervised Learning
Asynchronous Distributed Learning of Topic Models
No-Regret Learning in Bayesian Games
A Bayesian Approach to Data Point Selection
Evaluating State-of-the-Art Classification Models Against Bayes Optimality
Learning Shared Safety Constraints from Multi-task Demonstrations
Poisson-Gamma dynamical systems
CGLB: Benchmark Tasks for Continual Graph Learning
Semi-Truths: A Large-Scale Dataset of AI-Augmented Images for Evaluating Robustness of AI-Generated Image detectors
Equivariant Spatio-Temporal Attentive Graph Networks to Simulate Physical Dynamics
Information Regularization with Partially Labeled Data
Learning 3D Garment Animation from Trajectories of A Piece of Cloth
Learning Search Space Partition for Black-box Optimization using Monte Carlo Tree Search
Fair Allocation in Dynamic Mechanism Design
A Bayesian Data Augmentation Approach for Learning Deep Models
KERPLE: Kernelized Relative Positional Embedding for Length Extrapolation
Generalised Coupled Tensor Factorisation
Discovering Hierarchical Achievements in Reinforcement Learning via Contrastive Learning
Probabilistic Variational Bounds for Graphical Models
Reasoning With Neural Tensor Networks for Knowledge Base Completion
Game Design for Eliciting Distinguishable Behavior
Directional Smoothness and Gradient Methods: Convergence and Adaptivity
Hierarchical Selective Classification
Zero-Shot Clinical Acronym Expansion via Latent Meaning Cells
On the impact of activation and normalization in obtaining isometric embeddings at initialization
On the universality of deep learning
Adversarial Examples Might be Avoidable: The Role of Data Concentration in Adversarial Robustness
Adaptive Template Matching with Shift-Invariant Semi-NMF
Facilitating Graph Neural Networks with Random Walk on Simplicial Complexes
Contextual Models for Object Detection Using Boosted Random Fields
Saliency-based Sequential Image Attention with Multiset Prediction
Reinforced Few-Shot Acquisition Function Learning for Bayesian Optimization
Reconstructing Perceptive Images from Brain Activity by Shape-Semantic GAN
Visual Question Answering with Question Representation Update (QRU)
Efficient Sampling for Bipartite Matching Problems
LP-3DGS: Learning to Prune 3D Gaussian Splatting
Demographic Parity Constrained Minimax Optimal Regression under Linear Model
Dual Prototype Evolving for Test-Time Generalization of Vision-Language Models
Dynamic Environments with Deformable Objects
Near-Optimal Smoothing of Structured Conditional Probability Matrices
Learning Global Direct Inverse Kinematics
Attentional Pooling for Action Recognition
Identifying and Benchmarking Natural Out-of-Context Prediction Problems
Improved Algorithms for Convex-Concave Minimax Optimization
Contrastive dimension reduction: when and how?
PIVOT-R: Primitive-Driven Waypoint-Aware World Model for Robotic Manipulation
Tracking Dynamic Sources of Malicious Activity at Internet Scale
Stein Variational Gradient Descent: A General Purpose Bayesian Inference Algorithm
Test-time Training for Matching-based Video Object Segmentation
Multiclass Transductive Online Learning
Learning Loop Invariants for Program Verification
Sustainable Online Reinforcement Learning for Auto-bidding
Deeply Learned Spectral Total Variation Decomposition
Mapping Classifier Systems Into Neural Networks
Efficient Second Order Online Learning by Sketching
Compositional Generalization in Unsupervised Compositional Representation Learning: A Study on Disentanglement and Emergent Language
NeurIPS 2020 Competition and Demonstration Track, 6-12 December 2020, Virtual Event / Vancouver, BC, Canada
MixEval: Deriving Wisdom of the Crowd from LLM Benchmark Mixtures
Linear Causal Representation Learning from Unknown Multi-node Interventions
Fused sparsity and robust estimation for linear models with unknown variance
Random Quadratic Forms with Dependence: Applications to Restricted Isometry and Beyond
Alias-Free Mamba Neural Operator
Autoformer: Decomposition Transformers with Auto-Correlation for Long-Term Series Forecasting
Recursion in Recursion: Two-Level Nested Recursion for Length Generalization with Scalability
Deep Learning Models of the Retinal Response to Natural Scenes
Robust design of biological experiments
SVD-Softmax: Fast Softmax Approximation on Large Vocabulary Neural Networks
Interpretable Epilepsy Detection in Routine, Interictal EEG Data using Deep Learning
MonoSDF: Exploring Monocular Geometric Cues for Neural Implicit Surface Reconstruction
Spectral k-Support Norm Regularization
Punctuation-level Attack: Single-shot and Single Punctuation Can Fool Text Models
Accelerating Rescaled Gradient Descent: Fast Optimization of Smooth Functions
A provable control of sensitivity of neural networks through a direct parameterization of the overall bi-Lipschitzness
Theory of Self-Organization of Cortical Maps
Improved and Generalized Upper Bounds on the Complexity of Policy Iteration
Multidimensional Triangulation and Interpolation for Reinforcement Learning
Real-Time Motion Prediction via Heterogeneous Polyline Transformer with Relative Pose Encoding
Map It Anywhere: Empowering BEV Map Prediction using Large-scale Public Datasets
Communication Efficient Distributed Learning for Kernelized Contextual Bandits
Efficient Batched Algorithm for Contextual Linear Bandits with Large Action Space via Soft Elimination
Search-Guided, Lightly-Supervised Training of Structured Prediction Energy Networks
Identifying Alzheimer's Disease-Related Brain Regions from Multi-Modality Neuroimaging Data using Sparse Composite Linear Discrimination Analysis
Canonical Capsules: Self-Supervised Capsules in Canonical Pose
Comparison of Three Classification Techniques: CART, C4.5 and Multi-Layer Perceptrons
Credit Assignment through Time: Alternatives to Backpropagation
Learning Multi-agent Behaviors from Distributed and Streaming Demonstrations
Optimal Bayesian Recommendation Sets and Myopically Optimal Choice Query Sets
DeepInteraction: 3D Object Detection via Modality Interaction
Two-Stage Predict+Optimize for MILPs with Unknown Parameters in Constraints
Temporal Graph Neural Tangent Kernel with Graphon-Guaranteed
Clustering sequence sets for motif discovery
Supervised Dictionary Learning
Bayesian Model of Behaviour in Economic Games
Understanding Generalizability of Diffusion Models Requires Rethinking the Hidden Gaussian Structure
Distributed Training with Heterogeneous Data: Bridging Median- and Mean-Based Algorithms
Attention Bottlenecks for Multimodal Fusion
Semi-Implicit Denoising Diffusion Models (SIDDMs)
Directed Graph Embedding: an Algorithm based on Continuous Limits of Laplacian-type Operators
WOR and p 's: Sketches for ℓ p -Sampling Without Replacement
Cross-Modality Perturbation Synergy Attack for Person Re-identification
Self-Retrieval: End-to-End Information Retrieval with One Large Language Model
Joint M-Best-Diverse Labelings as a Parametric Submodular Minimization
Metric on Nonlinear Dynamical Systems with Perron-Frobenius Operators
Shadow Dirichlet for Restricted Probability Modeling
Optimizing Neural Networks via Koopman Operator Theory
Time-series Generation by Contrastive Imitation
Less-forgetting Multi-lingual Fine-tuning
Identity Uncertainty and Citation Matching
Visualizing the Loss Landscape of Neural Nets
Saliency-driven Experience Replay for Continual Learning
MoTE: Reconciling Generalization with Specialization for Visual-Language to Video Knowledge Transfer
Trustworthy Monte Carlo
Sparse Kernel Orthonormalized PLS for feature extraction in large data sets
Optimal Training Algorithms and their Relation to Backpropagation
United We Stand, Divided We Fall: Fingerprinting Deep Neural Networks via Adversarial Trajectories
Weakly Supervised Deep Functional Maps for Shape Matching
Leveraging Spatial and Temporal Correlations in Sparsified Mean Estimation
Zero-Shot Scene Reconstruction from Single Images with Deep Prior Assembly
MVInpainter: Learning Multi-View Consistent Inpainting to Bridge 2D and 3D Editing
Maximum Likelihood Training of Implicit Nonlinear Diffusion Model
Bayesian Optimistic Optimization: Optimistic Exploration for Model-based Reinforcement Learning
Structured flexibility in recurrent neural networks via neuromodulation
Block Sparse Bayesian Learning: A Diversified Scheme
Cross-Device Collaborative Test-Time Adaptation
Emergent Reciprocity and Team Formation from Randomized Uncertain Social Preferences
Edge Representation Learning with Hypergraphs
Blow: a single-scale hyperconditioned flow for non-parallel raw-audio voice conversion
Causally motivated multi-shortcut identification and removal
On the Representation of Solutions to Elliptic PDEs in Barron Spaces
Referring Human Pose and Mask Estimation In the Wild
Learning Language from Vision
Double Q-learning
Near Optimal Reconstruction of Spherical Harmonic Expansions
Can Language Models Teach? Teacher Explanations Improve Student Performance via Personalization
Retaining Beneficial Information from Detrimental Data for Neural Network Repair
Probabilistic Low-Rank Matrix Completion with Adaptive Spectral Regularization Algorithms
Capacity and Bias of Learned Geometric Embeddings for Directed Graphs
BehaviorGPT: Smart Agent Simulation for Autonomous Driving with Next-Patch Prediction
Rigorous Runtime Analysis of MOEA/D for Solving Multi-Objective Minimum Weight Base Problems
Iterative Amortized Policy Optimization
Learning from Positive and Unlabeled Data with Arbitrary Positive Shift
A Statistical Mechanics Approach to Approximate Analytical Bootstrap Averages
CryptoNAS: Private Inference on a ReLU Budget
Spectral Filtering for General Linear Dynamical Systems
Random Feature Stein Discrepancies
Globally Optimal Training of Generalized Polynomial Neural Networks with Nonlinear Spectral Methods