yusuke1997/dblp-id-title huggingface dataset:
Graph-based Discriminators: Sample Complexity and Expressiveness
Practical Shuffle Coding
Differentially private subspace clustering
Latent exploration for Reinforcement Learning
The Role of MT Neuron Receptive Field Surrounds in Computing Object Shape from Velocity Fields
Probabilistic Modeling of Dependencies Among Visual Short-Term Memory Representations
Lifelong Learning with Non-i.i.d. Tasks
Score-based generative models are provably robust: an uncertainty quantification perspective
Multiplicative Weights Update with Constant Step-Size in Congestion Games: Convergence, Limit Cycles and Chaos
Interpreting Representation Quality of DNNs for 3D Point Cloud Processing
Optimistic Optimization of a Deterministic Function without the Knowledge of its Smoothness
Prospective Representation Learning for Non-Exemplar Class-Incremental Learning
Adversarial Risk and Robustness: General Definitions and Implications for the Uniform Distribution
Improved Fine-Tuning by Better Leveraging Pre-Training Data
FS-Mol: A Few-Shot Learning Dataset of Molecules
Control of Selective Visual Attention: Modeling the Where Pathway
Message Passing Inference for Large Scale Graphical Models with High Order Potentials
VRA: Variational Rectified Activation for Out-of-distribution Detection
Unsupervised Multi-View Object Segmentation Using Radiance Field Propagation
Modeling High-Dimensional Discrete Data with Multi-Layer Neural Networks
Semi-supervised Learning using Sparse Eigenfunction Bases
A Non-linear Information Maximisation Algorithm that Performs Blind Separation
MEQA: A Benchmark for Multi-hop Event-centric Question Answering with Explanations
Conditional Matrix Flows for Gaussian Graphical Models
Curve Your Enthusiasm: Concurvity Regularization in Differentiable Generalized Additive Models
Random deep neural networks are biased towards simple functions
DRIP: Unleashing Diffusion Priors for Joint Foreground and Alpha Prediction in Image Matting
CEDe: A collection of expert-curated datasets with atom-level entity annotations for Optical Chemical Structure Recognition
Distributed Inference for Latent Dirichlet Allocation
Co-Generation with GANs using AIS based HMC
Data-dependent PAC-Bayes priors via differential privacy
Explicable Policy Search
Sub-optimal Experts mitigate Ambiguity in Inverse Reinforcement Learning
UniIF: Unified Molecule Inverse Folding
Variational Inference for Crowdsourcing
Flexible Option Learning
Variational Autoencoder for Deep Learning of Images, Labels and Captions
Robust On-Policy Sampling for Data-Efficient Policy Evaluation in Reinforcement Learning
Spatial-frequency channels, shape bias, and adversarial robustness
Automating Data Annotation under Strategic Human Agents: Risks and Potential Solutions
Stability and Generalization of the Decentralized Stochastic Gradient Descent Ascent Algorithm
Representing Face Images for Emotion Classification
Quantifying Aleatoric Uncertainty of the Treatment Effect: A Novel Orthogonal Learner
Learning Chordal Markov Networks by Constraint Satisfaction
Online Algorithms for Multi-shop Ski Rental with Machine Learned Advice
IMAGPose: A Unified Conditional Framework for Pose-Guided Person Generation
Bounded rationality in structured density estimation
FedGMark: Certifiably Robust Watermarking for Federated Graph Learning
TabNAS: Rejection Sampling for Neural Architecture Search on Tabular Datasets
Training and Inference on Any-Order Autoregressive Models the Right Way
Efficient Optimization for Linear Dynamical Systems with Applications to Clustering and Sparse Coding
Inferring sparse representations of continuous signals with continuous orthogonal matching pursuit
PointNet++: Deep Hierarchical Feature Learning on Point Sets in a Metric Space
An Analysis of Constant Step Size SGD in the Non-convex Regime: Asymptotic Normality and Bias
Expert load matters: operating networks at high accuracy and low manual effort
Minimax Localization of Structural Information in Large Noisy Matrices
Generalization Analysis for Label-Specific Representation Learning
Learning Multi-level Sparse Representations
NeuralSteiner: Learning Steiner Tree for Overflow-avoiding Global Routing in Chip Design
MADLAD-400: A Multilingual And Document-Level Large Audited Dataset
KONG: Kernels for ordered-neighborhood graphs
Learning in Non-Cooperative Configurable Markov Decision Processes
SoteriaFL: A Unified Framework for Private Federated Learning with Communication Compression
Secure Multi-party Differential Privacy
Stable-Pose: Leveraging Transformers for Pose-Guided Text-to-Image Generation
Adversarial Prediction Games for Multivariate Losses
Revisit Multimodal Meta-Learning through the Lens of Multi-Task Learning
Temporal Difference Learning of Position Evaluation in the Game of Go
Adaptive Data Analysis in a Balanced Adversarial Model
Self-Supervised MultiModal Versatile Networks
Feudal Reinforcement Learning
M-FAC: Efficient Matrix-Free Approximations of Second-Order Information
Avoiding Side Effects in Complex Environments
Optimal cue selection strategy
Adaptively Aligned Image Captioning via Adaptive Attention Time
No-Regret Learning for Fair Multi-Agent Social Welfare Optimization
Derivative Estimation in Random Design
Algorithmic Stability and Uniform Generalization
Learning Universal Policies via Text-Guided Video Generation
Learning Active Camera for Multi-Object Navigation
Embedding Inference for Structured Multilabel Prediction
Learning Mask-aware CLIP Representations for Zero-Shot Segmentation
Benchmarking Estimators for Natural Experiments: A Novel Dataset and a Doubly Robust Algorithm
Rethinking Importance Weighting for Deep Learning under Distribution Shift
Training Quantized Nets: A Deeper Understanding
Near-optimal Reinforcement Learning in Factored MDPs
On the Curved Geometry of Accelerated Optimization
Induction in Neuroscience with Classification: Issues and Solutions
Progressive Entropic Optimal Transport Solvers
A contrastive rule for meta-learning
Decentralized Langevin Dynamics for Bayesian Learning
Provable Partially Observable Reinforcement Learning with Privileged Information
Integrating Expert ODEs into Neural ODEs: Pharmacology and Disease Progression
Stronger NAS with Weaker Predictors
A Closer Look at Offline RL Agents
NN-Baker: A Neural-network Infused Algorithmic Framework for Optimization Problems on Geometric Intersection Graphs
Does Knowledge Distillation Really Work?
Effective Diversity in Population Based Reinforcement Learning
Constructing Topological Maps using Markov Random Fields and Loop-Closure Detection
How Transformers Utilize Multi-Head Attention in In-Context Learning? A Case Study on Sparse Linear Regression
TRAFFIC: Recognizing Objects Using Hierarchical Reference Frame Transformations
Stabilizing Zero-Shot Prediction: A Novel Antidote to Forgetting in Continual Vision-Language Tasks
BoardgameQA: A Dataset for Natural Language Reasoning with Contradictory Information
Model-Based Reparameterization Policy Gradient Methods: Theory and Practical Algorithms
Towards Understanding Acceleration Tradeoff between Momentum and Asynchrony in Nonconvex Stochastic Optimization
CAP: Correlation-Aware Pruning for Highly-Accurate Sparse Vision Models
Gradient Episodic Memory for Continual Learning
Approximate Analytical Bootstrap Averages for Support Vector Classifiers
Predictive Q-Routing: A Memory-based Reinforcement Learning Approach to Adaptive Traffic Control
A Four Neuron Circuit Accounts for Change Sensitive Inhibition in Salamander Retina
Causal Inference via Kernel Deviance Measures
Variational Bayesian Optimistic Sampling
The committee machine: Computational to statistical gaps in learning a two-layers neural network
On the Concentration of Spectral Properties
Generating Training Data with Language Models: Towards Zero-Shot Language Understanding
GAP Safe screening rules for sparse multi-task and multi-class models
A Model of the Phonological Loop: Generalization and Binding
Switching Autoregressive Low-rank Tensor Models
OwMatch: Conditional Self-Labeling with Consistency for Open-World Semi-Supervised Learning
Credal Marginal MAP
Meta Architecture Search
Do's and Don'ts: Learning Desirable Skills with Instruction Videos
Causal Inference with Non-IID Data using Linear Graphical Models
SLIM: Style-Linguistics Mismatch Model for Generalized Audio Deepfake Detection
Fully Dynamic Consistent Facility Location
On the Circuit Complexity of Neural Networks
Generating Correct Answers for Progressive Matrices Intelligence Tests
Cal-QL: Calibrated Offline RL Pre-Training for Efficient Online Fine-Tuning
Viewing Classifier Systems as Model Free Learning in POMDPs
Making AI Forget You: Data Deletion in Machine Learning
Online Convex Optimization with Continuous Switching Constraint
Synchronization can Control Regularization in Neural Systems via Correlated Noise Processes
On Causal Discovery in the Presence of Deterministic Relations
FLuID: Mitigating Stragglers in Federated Learning using Invariant Dropout
Topology-Aware Uncertainty for Image Segmentation
Analog Soft-Pattern-Matching Classifier using Floating-Gate MOS Technology
Blind Separation of Radio Signals in Fading Channels
An Analysis of Inference with the Universum
Single-Model Uncertainties for Deep Learning
Max-Margin Majority Voting for Learning from Crowds
N-Gram Graph: Simple Unsupervised Representation for Graphs, with Applications to Molecules
Dual-Free Stochastic Decentralized Optimization with Variance Reduction
Fast Vision Transformers with HiLo Attention
Tight Bounds for Volumetric Spanners and Applications
Online Deep Equilibrium Learning for Regularization by Denoising
Approximating Equilibria in Sequential Auctions with Incomplete Information and Multi-Unit Demand
A Stein variational Newton method
SEGA: Instructing Text-to-Image Models using Semantic Guidance
Learning Collaborative Policies to Solve NP-hard Routing Problems
Rectangular Flows for Manifold Learning
Oja's Algorithm for Streaming Sparse PCA
Identifying Functionally Important Features with End-to-End Sparse Dictionary Learning
Single-Loop Stochastic Algorithms for Difference of Max-Structured Weakly Convex Functions
Resolving Discrepancies in Compute-Optimal Scaling of Language Models
On Learning Decision Heuristics
Transductive Active Learning: Theory and Applications
An Information-Theoretic Approach to Deciphering the Hippocampal Code
Sparse Deep Learning for Time Series Data: Theory and Applications
Blind channel identification for speech dereverberation using l1-norm sparse learning
Dict-TTS: Learning to Pronounce with Prior Dictionary Knowledge for Text-to-Speech
Generalizing Goal-Conditioned Reinforcement Learning with Variational Causal Reasoning
Learning Bayesian networks with ancestral constraints
Maximum Entropy Monte-Carlo Planning
Weakly Coupled Deep Q-Networks
Expectile Regularization for Fast and Accurate Training of Neural Optimal Transport
Direct Feedback Alignment Scales to Modern Deep Learning Tasks and Architectures
GBA: A Tuning-free Approach to Switch between Synchronous and Asynchronous Training for Recommendation Models
Grouping-Based Low-Rank Trajectory Completion and 3D Reconstruction
Hierarchical Channel-spatial Encoding for Communication-efficient Collaborative Learning
DETOX: A Redundancy-based Framework for Faster and More Robust Gradient Aggregation
Using Noise to Infer Aspects of Simplicity Without Learning
The Return of the Gating Network: Combining Generative Models and Discriminative Training in Natural Image Priors
Generalized Logit Adjustment: Calibrating Fine-tuned Models by Removing Label Bias in Foundation Models
Toward a realistic model of speech processing in the brain with self-supervised learning
Spherical Channels for Modeling Atomic Interactions
Greedy Layer-Wise Training of Deep Networks
Cooperative neural networks (CoNN): Exploiting prior independence structure for improved classification
Advances in Neural Information Processing Systems 21, Proceedings of the Twenty-Second Annual Conference on Neural Information Processing Systems, Vancouver, British Columbia, Canada, December 8-11, 2008
Towards Efficient and Effective Adversarial Training
An Empirical Investigation of Representation Learning for Imitation
Reliable Learning of Halfspaces under Gaussian Marginals
A Neural Network Classifier Based on Coding Theory
SciFIBench: Benchmarking Large Multimodal Models for Scientific Figure Interpretation
Learning to combine foveal glimpses with a third-order Boltzmann machine
ComMU: Dataset for Combinatorial Music Generation
How and Why to Manipulate Your Own Agent: On the Incentives of Users of Learning Agents
Reversible and irreversible bracket-based dynamics for deep graph neural networks
Towards Context-Agnostic Learning Using Synthetic Data
INDIGO: GNN-Based Inductive Knowledge Graph Completion Using Pair-Wise Encoding
Mildly Conservative Q-Learning for Offline Reinforcement Learning
A Communication-Efficient Distributed Gradient Clipping Algorithm for Training Deep Neural Networks
Front-door Adjustment Beyond Markov Equivalence with Limited Graph Knowledge
Deep Symmetry Networks
HourVideo: 1-Hour Video-Language Understanding
Fast greedy algorithms for dictionary selection with generalized sparsity constraints
EigenVI: score-based variational inference with orthogonal function expansions
Algorithms for Better Representation and Faster Learning in Radial Basis Function Networks
Online Learning and Pricing for Network Revenue Management with Reusable Resources
Precision-Recall-Gain Curves: PR Analysis Done Right
Inference with Multivariate Heavy-Tails in Linear Models
Datasets and Benchmarks for Nanophotonic Structure and Parametric Design Simulations
Neural decoding from stereotactic EEG: accounting for electrode variability across subjects
Outlier Robust Mean Estimation with Subgaussian Rates via Stability
Improved Guarantees for k-means++ and k-means++ Parallel
Preventing Dimensional Collapse in Self-Supervised Learning via Orthogonality Regularization
Improved Algorithms for Collaborative PAC Learning
English Alphabet Recognition with Telephone Speech
Limits in Learning Machine Accuracy Imposed by Data Quality
On the Benefits of Public Representations for Private Transfer Learning under Distribution Shift
Learning with Tree-Averaged Densities and Distributions
Cholinergic suppression of transmission may allow combined associative memory function and self-organization in the neocortex
Propagating Knowledge Updates to LMs Through Distillation
An MDP-Based Approach to Online Mechanism Design
Ouroboros: On Accelerating Training of Transformer-Based Language Models
Unsupervised Object Detection with Theoretical Guarantees
Shaping Social Activity by Incentivizing Users
Bayesian morphometry of hippocampal cells suggests same-cell somatodendritic repulsion
Generalization of Back propagation to Recurrent and Higher Order Neural Networks
Learning Interpretable Decision Rule Sets: A Submodular Optimization Approach
Alternation makes the adversary weaker in two-player games
Improved Regret for Bandit Convex Optimization with Delayed Feedback
Kullback-Leibler Maillard Sampling for Multi-armed Bandits with Bounded Rewards
$\alpha$-IoU: A Family of Power Intersection over Union Losses for Bounding Box Regression
Exploratory Data Analysis Using Radial Basis Function Latent Variable Models
Source Separation and Density Estimation by Faithful Equivariant SOM
Geometric Order Learning for Rank Estimation
Flow-Based Feature Fusion for Vehicle-Infrastructure Cooperative 3D Object Detection
Coherent Hierarchical Multi-Label Classification Networks
Hybrid Mamba for Few-Shot Segmentation
Sparse Manifold Clustering and Embedding
k-Means Clustering with Distance-Based Privacy
Convergence rates of sub-sampled Newton methods
Semi-supervisedly Co-embedding Attributed Networks
Jailbreaking Large Language Models Against Moderation Guardrails via Cipher Characters
Categorization Under Complexity: A Unified MDL Account of Human Learning of Regular and Irregular Categories
Competitive Anti-Hebbian Learning of Invariants
Learning Better with Less: Effective Augmentation for Sample-Efficient Visual Reinforcement Learning
TaskMet: Task-driven Metric Learning for Model Learning
ACES: Generating a Diversity of Challenging Programming Puzzles with Autotelic Generative Models
Bi-Objective Online Matching and Submodular Allocations
Optimizing F-Measures by Cost-Sensitive Classification
Global Convergence of Deep Networks with One Wide Layer Followed by Pyramidal Topology
Rejection via Learning Density Ratios
Distributional Policy Optimization: An Alternative Approach for Continuous Control
Learning Layer-wise Equivariances Automatically using Gradients
Sleeper Agent: Scalable Hidden Trigger Backdoors for Neural Networks Trained from Scratch
Uplifting Bandits
Semi-Supervised Learning for Optical Flow with Generative Adversarial Networks
A General Projection Property for Distribution Families
Block Variable Selection in Multivariate Regression and High-dimensional Causal Inference
Geometrically Coupled Monte Carlo Sampling
Model-based targeted dimensionality reduction for neuronal population data
Green Hierarchical Vision Transformer for Masked Image Modeling
Self-Calibrated Tuning of Vision-Language Models for Out-of-Distribution Detection
Predictive inference is free with the jackknife+-after-bootstrap
Using body-anchored priors for identifying actions in single images
FedFed: Feature Distillation against Data Heterogeneity in Federated Learning
Why So Pessimistic? Estimating Uncertainties for Offline RL through Ensembles, and Why Their Independence Matters
Fairness in Multi-Agent Sequential Decision-Making
Rapid Model Architecture Adaption for Meta-Learning
Simple and Effective Masked Diffusion Language Models
Super-Resolution Off the Grid
MmCows: A Multimodal Dataset for Dairy Cattle Monitoring
Intruding with Words: Towards Understanding Graph Injection Attacks at the Text Level
Tree Mover's Distance: Bridging Graph Metrics and Stability of Graph Neural Networks
Using a Logarithmic Mapping to Enable Lower Discount Factors in Reinforcement Learning
On Provable Benefits of Depth in Training Graph Convolutional Networks
Towards Self-Interpretable Graph-Level Anomaly Detection
Infinite Relational Modeling of Functional Connectivity in Resting State fMRI
ImageBART: Bidirectional Context with Multinomial Diffusion for Autoregressive Image Synthesis
Visual Motion Computation in Analog VLSI Using Pulses
MAU: A Motion-Aware Unit for Video Prediction and Beyond
Stochastic Variance Reduction Methods for Saddle-Point Problems
SimVG: A Simple Framework for Visual Grounding with Decoupled Multi-modal Fusion
On-Road Object Importance Estimation: A New Dataset and A Model with Multi-Fold Top-Down Guidance
MMScan: A Multi-Modal 3D Scene Dataset with Hierarchical Grounded Language Annotations
Unsupervised Learning of View-invariant Action Representations
Tensor Switching Networks
Deconstructing Data Reconstruction: Multiclass, Weight Decay and General Losses
Nearly Optimal Private LASSO
Tractable Operations for Arithmetic Circuits of Probabilistic Models
Instruction Embedding: Latent Representations of Instructions Towards Task Identification
HyperSPNs: Compact and Expressive Probabilistic Circuits
Invariant Causal Imitation Learning for Generalizable Policies
Measuring Invariances in Deep Networks
Disentangling Human Error from Ground Truth in Segmentation of Medical Images
Amplifying Membership Exposure via Data Poisoning
Economic Properties of Social Networks
Preventing Model Collapse in Deep Canonical Correlation Analysis by Noise Regularization
Kernel PCA and De-Noising in Feature Spaces
InstructG2I: Synthesizing Images from Multimodal Attributed Graphs
Beta Diffusion
Correlation clustering with local objectives
HPO-B: A Large-Scale Reproducible Benchmark for Black-Box HPO based on OpenML
Analog Neural Networks of Limited Precision I: Computing with Multilinear Threshold Functions
Adversarial Robustness with Non-uniform Perturbations
A Topological Perspective on Causal Inference
Hierarchical Programmatic Option Framework
Weak-shot Fine-grained Classification via Similarity Transfer
Constrained Diffusion Models via Dual Training
Query-Aware MCMC
Improving Self-supervised Learning with Automated Unsupervised Outlier Arbitration
A Criterion for the Convergence of Learning with Spike Timing Dependent Plasticity
Computing the Bias of Constant-step Stochastic Approximation with Markovian Noise
Broadband Direction-Of-Arrival Estimation Based on Second Order Statistics
Stimulative Training of Residual Networks: A Social Psychology Perspective of Loafing
A-FedPD: Aligning Dual-Drift is All Federated Primal-Dual Learning Needs
Learning to Estimate Scenes from Images
Mixture of Link Predictors on Graphs
Multi-Label Learning with Stronger Consistency Guarantees
SplineNets: Continuous Neural Decision Graphs
Fast Training of Support Vector Classifiers
The topographic unsupervised learning of natural sounds in the auditory cortex
Shadow Knowledge Distillation: Bridging Offline and Online Knowledge Transfer
Learning Linear Dynamical Systems via Spectral Filtering
Neural P 3 M: A Long-Range Interaction Modeling Enhancer for Geometric GNNs
Secure Out-of-Distribution Task Generalization with Energy-Based Models
Information Diffusion Kernels
A Cost-Shaping LP for Bellman Error Minimization with Performance Guarantees
Explainable Semantic Space by Grounding Language to Vision with Cross-Modal Contrastive Learning
An Analog VLSI Chip for Radial Basis Functions
Deep Neural Collapse Is Provably Optimal for the Deep Unconstrained Features Model
A PAC-Bayes Risk Bound for General Loss Functions
Interpretable Graph Networks Formulate Universal Algebra Conjectures
UQGAN: A Unified Model for Uncertainty Quantification of Deep Classifiers trained via Conditional GANs
Few-Shot Segmentation via Cycle-Consistent Transformer
Toward Re-Identifying Any Animal
Curriculum Learning for Graph Neural Networks: Which Edges Should We Learn First
The Poisson Midpoint Method for Langevin Dynamics: Provably Efficient Discretization for Diffusion Models
Advances in Neural Information Processing Systems 10, [NIPS Conference, Denver, Colorado, USA, 1997]
Model Sparsity Can Simplify Machine Unlearning
Beating SGD Saturation with Tail-Averaging and Minibatching
Non-parametric classification via expand-and-sparsify representation
Variational Mixture-of-Experts Autoencoders for Multi-Modal Deep Generative Models
Boosting with Tempered Exponential Measures
Rethinking The Training And Evaluation of Rich-Context Layout-to-Image Generation
FIRAL: An Active Learning Algorithm for Multinomial Logistic Regression
Modelling Spatial Recall, Mental Imagery and Neglect
Simultaneously Leveraging Output and Task Structures for Multiple-Output Regression
BOME! Bilevel Optimization Made Easy: A Simple First-Order Approach
The Consistency of Common Neighbors for Link Prediction in Stochastic Blockmodels
Working hard to know your neighbor's margins: Local descriptor learning loss
A Bayesian Approach for Policy Learning from Trajectory Preference Queries
Unity by Diversity: Improved Representation Learning for Multimodal VAEs
Temporal Regularization for Markov Decision Process
Local Gaussian Process Regression for Real Time Online Model Learning
Restricted Boltzmann machines modeling human choice
Multimodal single cell data integration challenge: Results and lessons learned
Neural-Logic Human-Object Interaction Detection
SEL-BALD: Deep Bayesian Active Learning with Selective Labels
Divide-and-Conquer Meets Consensus: Unleashing the Power of Functions in Code Generation
Fitting Low-Rank Tensors in Constant Time
Time Series as Images: Vision Transformer for Irregularly Sampled Time Series
Beta-CROWN: Efficient Bound Propagation with Per-neuron Split Constraints for Neural Network Robustness Verification
Test-Time Adaptation Induces Stronger Accuracy and Agreement-on-the-Line
Offline Minimax Soft-Q-learning Under Realizability and Partial Coverage
Rethinking Individual Global Max in Cooperative Multi-Agent Reinforcement Learning
On Ranking in Survival Analysis: Bounds on the Concordance Index
Distributed Occlusion Reasoning for Tracking with Nonparametric Belief Propagation
Variational Inference for Bayesian Mixtures of Factor Analysers
Ultrametric Fitting by Gradient Descent