yusuke1997/dblp-id-title huggingface dataset:
DRUM: End-To-End Differentiable Rule Mining On Knowledge Graphs
Object-centric Learning with Cyclic Walks between Parts and Whole
Efficient Sampling on Riemannian Manifolds via Langevin MCMC
LaFTer: Label-Free Tuning of Zero-shot Classifier using Language and Unlabeled Image Collections
Geometry-Informed Neural Operator for Large-Scale 3D PDEs
What Makes Data Suitable for a Locally Connected Neural Network? A Necessary and Sufficient Condition Based on Quantum Entanglement
Learning with Local and Global Consistency
Certifying Some Distributional Fairness with Subpopulation Decomposition
DUOL: A Double Updating Approach for Online Learning
Game Theoretic Algorithms for Protein-DNA binding
Semi-supervised Learning with Penalized Probabilistic Clustering
Parameterized Novelty Detectors for Environmental Sensor Monitoring
Neural Approach for TV Image Compression Using a Hopfield Type Network
Visual Memory for Robust Path Following
Factor Modeling for Advertisement Targeting
Reinforcement Learning in Linear MDPs: Constant Regret and Representation Selection
Policy Regret in Repeated Games
Glance-and-Gaze Vision Transformer
The Stability-Efficiency Dilemma: Investigating Sequence Length Warmup for Training GPT Models
Capacity and Information Efficiency of a Brain-like Associative Net
Robust Correction of Sampling Bias using Cumulative Distribution Functions
Nonparametric inference of prior probabilities from Bayes-optimal behavior
HORSE: Hierarchical Representation for Large-Scale Neural Subset Selection
Correlation Clustering with Adaptive Similarity Queries
Learnable Fourier Features for Multi-dimensional Spatial Positional Encoding
Noisy Ostracods: A Fine-Grained, Imbalanced Real-World Dataset for Benchmarking Robust Machine Learning and Label Correction Methods
AverNet: All-in-one Video Restoration for Time-varying Unknown Degradations
Estimating Learning Effects: A Short-Time Fourier Transform Regression Model for MEG Source Localization
Multimodal Residual Learning for Visual QA
DNA: Proximal Policy Optimization with a Dual Network Architecture
A Provably Efficient Model-Free Posterior Sampling Method for Episodic Reinforcement Learning
Open-set Label Noise Can Improve Robustness Against Inherent Label Noise
Hypernetwork-based Meta-Learning for Low-Rank Physics-Informed Neural Networks
Universal Graph Convolutional Networks
Beyond NTK with Vanilla Gradient Descent: A Mean-Field Analysis of Neural Networks with Polynomial Width, Samples, and Time
Probabilistic Low-Rank Subspace Clustering
Optimal Manifold Representation of Data: An Information Theoretic Approach
The Importance of Online Data: Understanding Preference Fine-tuning via Coverage
SynthBio: A Case Study in Faster Curation of Text Datasets
Efficient Online Learning of Optimal Rankings: Dimensionality Reduction via Gradient Descent
Information Factorization in Connectionist Models of Perception
Moonshine: Distilling with Cheap Convolutions
Star-Shaped Denoising Diffusion Probabilistic Models
Risk-Averse Model Uncertainty for Distributionally Robust Safe Reinforcement Learning
Data-Efficient GAN Training Beyond (Just) Augmentations: A Lottery Ticket Perspective
1-norm Support Vector Machines
Online Pricing for Multi-User Multi-Item Markets
IncomeSCM: From tabular data set to time-series simulator and causal estimation benchmark
Online Learning of Optimal Bidding Strategy in Repeated Multi-Commodity Auctions
Robust Classification Under Sample Selection Bias
Bayesian Optimization under Heavy-tailed Payoffs
Functional Regularization for Reinforcement Learning via Learned Fourier Features
Learning Equivariant Segmentation with Instance-Unique Querying
Online Influence Maximization under Independent Cascade Model with Semi-Bandit Feedback
Matrix Manifold Optimization for Gaussian Mixtures
FedAvP: Augment Local Data via Shared Policy in Federated Learning
Unsupervised feature learning for audio classification using convolutional deep belief networks
Auslan-Daily: Australian Sign Language Translation for Daily Communication and News
From Lasso regression to Feature vector machine
Decentralized, Communication- and Coordination-free Learning in Structured Matching Markets
Transfer Learning from Speaker Verification to Multispeaker Text-To-Speech Synthesis
LCGen: Mining in Low-Certainty Generation for View-consistent Text-to-3D
Frozen-DETR: Enhancing DETR with Image Understanding from Frozen Foundation Models
Semi-Supervised Video Salient Object Detection Based on Uncertainty-Guided Pseudo Labels
Locally Invariant Explanations: Towards Stable and Unidirectional Explanations through Local Invariant Learning
Causal Identification with Matrix Equations
Visual Object Networks: Image Generation with Disentangled 3D Representations
Efficient constrained sampling via the mirror-Langevin algorithm
Stability of Random Forests and Coverage of Random-Forest Prediction Intervals
Unsupervised Learning of Visual Features by Contrasting Cluster Assignments
High Density Associative Memories
Speeding Learning: Preface
Learning a Continuous Hidden Variable Model for Binary Data
XTC: Extreme Compression for Pre-trained Transformers Made Simple and Efficient
Reinforcement Learning based Disease Progression Model for Alzheimer's Disease
Accurate, reliable and fast robustness evaluation
Hunting for Discriminatory Proxies in Linear Regression Models
Kernel Choice and Classifiability for RKHS Embeddings of Probability Distributions
Heavy Ball Momentum for Conditional Gradient
SySCD: A System-Aware Parallel Coordinate Descent Algorithm
Neural Temporal Walks: Motif-Aware Representation Learning on Continuous-Time Dynamic Graphs
Panoptic 3D Scene Reconstruction From a Single RGB Image
Cooperative Distribution Alignment via JSD Upper Bound
Proximity Effect Corrections in Electron Beam Lithography
High-dimensional regression with noisy and missing data: Provable guarantees with non-convexity
REASONER: An Explainable Recommendation Dataset with Comprehensive Labeling Ground Truths
Computational and Statistical Tradeoffs in Learning to Rank
Efficient Policy Adaptation with Contrastive Prompt Ensemble for Embodied Agents
Adversarial Robustness with Semi-Infinite Constrained Learning
Normalizing flow neural networks by JKO scheme
UniT: A Unified Look at Certified Robust Training against Text Adversarial Perturbation
Inference by Reparameterization in Neural Population Codes
Time-series Generative Adversarial Networks
Honor of Kings Arena: an Environment for Generalization in Competitive Reinforcement Learning
Sparse Deep Learning: A New Framework Immune to Local Traps and Miscalibration
Model Inversion Networks for Model-Based Optimization
Data Distributional Properties Drive Emergent In-Context Learning in Transformers
Learning on a General Network
Wasserstein distributional robustness of neural networks
Few-Shot Fast-Adaptive Anomaly Detection
ChessGPT: Bridging Policy Learning and Language Modeling
Learning to Rank by Optimizing NDCG Measure
H-InDex: Visual Reinforcement Learning with Hand-Informed Representations for Dexterous Manipulation
Unifying Generation and Prediction on Graphs with Latent Graph Diffusion
Scan Strategies for Meteorological Radars
Generative Models for Graph-Based Protein Design
Data-Driven Modeling of BOLD Drug Response Curves Using Gaussian Process Learning
Manifold Regularization for SIR with Rate Root-n Convergence
Minimax Bounds for Generalized Linear Models
Slice sampling covariance hyperparameters of latent Gaussian models
Provable Variational Inference for Constrained Log-Submodular Models
Big Self-Supervised Models are Strong Semi-Supervised Learners
Model Rubik's Cube: Twisting Resolution, Depth and Width for TinyNets
Biologically-plausible backpropagation through arbitrary timespans via local neuromodulators
Offline Reinforcement Learning for Mixture-of-Expert Dialogue Management
The Query Complexity of Cake Cutting
STL: Still Tricky Logic (for System Validation, Even When Showing Your Work)
Distilling Object Detectors with Feature Richness
Multivariate Stochastic Dominance via Optimal Transport and Applications to Models Benchmarking
Iterative Learning for Reliable Crowdsourcing Systems
The Effect of Correlations on the Fisher Information of Population Codes
Multilinear Mixture of Experts: Scalable Expert Specialization through Factorization
On the Computational Complexity of Networks of Spiking Neurons
Panchromatic and Multispectral Image Fusion via Alternating Reverse Filtering Network
Biologically Inspired Dynamic Thresholds for Spiking Neural Networks
Symbolic Dynamic Programming for Continuous State and Observation POMDPs
Optimal context separation of spiking haptic signals by second-order somatosensory neurons
NeoRL: A Near Real-World Benchmark for Offline Reinforcement Learning
Bayesian Deep Ensembles via the Neural Tangent Kernel
Variational PDEs for Acceleration on Manifolds and Application to Diffeomorphisms
CentripetalText: An Efficient Text Instance Representation for Scene Text Detection
Learning Mixtures of Plackett-Luce Models from Structured Partial Orders
Sparse Uncertainty Representation in Deep Learning with Inducing Weights
Towards Evaluating Transfer-based Attacks Systematically, Practically, and Fairly
Compacting, Picking and Growing for Unforgetting Continual Learning
Multimodal Large Language Models Make Text-to-Image Generative Models Align Better
Balancing information exposure in social networks
Learning Infinitesimal Generators of Continuous Symmetries from Data
Cricket Wind Detection
Unbounded cache model for online language modeling with open vocabulary
Conservative Data Sharing for Multi-Task Offline Reinforcement Learning
Training Binary Neural Networks via Gaussian Variational Inference and Low-Rank Semidefinite Programming
Dual Decomposed Learning with Factorwise Oracle for Structural SVM of Large Output Domain
Near-Optimal Randomized Exploration for Tabular Markov Decision Processes
RH-BrainFS: Regional Heterogeneous Multimodal Brain Networks Fusion Strategy
Dynamics of Generalization in Linear Perceptrons
A Method for the Associative Storage of Analog Vectors
Fairness Behind a Veil of Ignorance: A Welfare Analysis for Automated Decision Making
Factored Adaptation for Non-Stationary Reinforcement Learning
Avoiding Side Effects By Considering Future Tasks
Abstraction based Output Range Analysis for Neural Networks
Personalized Adapter for Large Meteorology Model on Devices: Towards Weather Foundation Models
The Effects of Circuit Integration on a Feature Map Vector Quantizer
Single-Pass Pivot Algorithm for Correlation Clustering. Keep it simple!
REVIVE: Regional Visual Representation Matters in Knowledge-Based Visual Question Answering
Q-Pain: A Question Answering Dataset to Measure Social Bias in Pain Management
Brownian Noise Reduction: Maximizing Privacy Subject to Accuracy Constraints
A Divide-and-Conquer Method for Sparse Inverse Covariance Estimation
Generalization Analysis on Learning with a Concurrent Verifier
Principal Geodesic Analysis for Probability Measures under the Optimal Transport Metric
Learning the context of a category
b-Bit Minwise Hashing for Estimating Three-Way Similarities
ZOPP: A Framework of Zero-shot Offboard Panoptic Perception for Autonomous Driving
Guiding Neural Collapse: Optimising Towards the Nearest Simplex Equiangular Tight Frame
Lost in Latent Space: Examining failures of disentangled models at combinatorial generalisation
The Robustness of Estimator Composition
SchNet: A continuous-filter convolutional neural network for modeling quantum interactions
ConRad: Image Constrained Radiance Fields for 3D Generation from a Single Image
Deep Structured Prediction with Nonlinear Output Transformations
Federated Learning from Pre-Trained Models: A Contrastive Learning Approach
Markov Processes on Curves for Automatic Speech Recognition
fMRI predictors based on language models of increasing complexity recover brain left lateralization
Proportional Participatory Budgeting with Additive Utilities
Replacing supervised classification learning by Slow Feature Analysis in spiking neural networks
3 state neurons for contextual processing
Large Language Models can Implement Policy Iteration
XMask3D: Cross-modal Mask Reasoning for Open Vocabulary 3D Semantic Segmentation
Unsupervised Learning for Solving the Travelling Salesman Problem
Beyond Confidence: Reliable Models Should Also Consider Atypicality
Joint inference and input optimization in equilibrium networks
Capturing implicit hierarchical structure in 3D biomedical images with self-supervised hyperbolic representations
Efficient Communication in Multi-Agent Reinforcement Learning via Variance Based Control
Learning to Predict Structural Vibrations
Synthetic Model Combination: An Instance-wise Approach to Unsupervised Ensemble Learning
Extraction of Temporal Features in the Electrosensory System of Weakly Electric Fish
Alchemy: A benchmark and analysis toolkit for meta-reinforcement learning agents
A Self-Tuning Actor-Critic Algorithm
Link Discovery using Graph Feature Tracking
FINE Samples for Learning with Noisy Labels
On the Theory of Learnining with Privileged Information
A* Sampling
A Boosting-Type Convergence Result for AdaBoost.MH with Factorized Multi-Class Classifiers
Moment Distributionally Robust Tree Structured Prediction
Fed-FA: Theoretically Modeling Client Data Divergence for Federated Language Backdoor Defense
Randomized Prior Functions for Deep Reinforcement Learning
RMIX: Learning Risk-Sensitive Policies for Cooperative Reinforcement Learning Agents
Scalable Influence Estimation in Continuous-Time Diffusion Networks
Aligning LLM Agents by Learning Latent Preference from User Edits
HW-GPT-Bench: Hardware-Aware Architecture Benchmark for Language Models
Aligning Diffusion Behaviors with Q-functions for Efficient Continuous Control
Bayesian Pseudocoresets
Reinforcement Learning for Continuous Stochastic Control Problems
Confidence-Aware Imitation Learning from Demonstrations with Varying Optimality
Learning with Hypergraphs: Clustering, Classification, and Embedding
Mitigating Spurious Correlations via Disagreement Probability
DiffusionFake: Enhancing Generalization in Deepfake Detection via Guided Stable Diffusion
A graph similarity for deep learning
Tree! I am no Tree! I am a low dimensional Hyperbolic Embedding
Chirality Nets for Human Pose Regression
Optimized Pre-Processing for Discrimination Prevention
Estimation and Imputation in Probabilistic Principal Component Analysis with Missing Not At Random Data
On quantum backpropagation, information reuse, and cheating measurement collapse
CMMA: Benchmarking Multi-Affection Detection in Chinese Multi-Modal Conversations
An Analysis of Ensemble Sampling
Mapping Tractography Across Subjects
A rational decision making framework for inhibitory control
When is an Integrate-and-fire Neuron like a Poisson Neuron?
Extracting low-dimensional dynamics from multiple large-scale neural population recordings by learning to predict correlations
Co-regularization Based Semi-supervised Domain Adaptation
How Data Augmentation affects Optimization for Linear Regression
Adversarial Sparse Transformer for Time Series Forecasting
Hierarchical Fisher Kernels for Longitudinal Data
4Real: Towards Photorealistic 4D Scene Generation via Video Diffusion Models
SPARKLE: A Unified Single-Loop Primal-Dual Framework for Decentralized Bilevel Optimization
TMT-VIS: Taxonomy-aware Multi-dataset Joint Training for Video Instance Segmentation
Representing Part-Whole Relationships in Recurrent Neural Networks
FALKON: An Optimal Large Scale Kernel Method
The CLIP Model is Secretly an Image-to-Prompt Converter
Closing the Computational-Statistical Gap in Best Arm Identification for Combinatorial Semi-bandits
Localizing 3D cuboids in single-view images
When Worlds Collide: Integrating Different Counterfactual Assumptions in Fairness
Which Mutual-Information Representation Learning Objectives are Sufficient for Control?
On the Dynamics of Boosting
Debiased Contrastive Learning
Gaussian Process Volatility Model
Local Latent Space Bayesian Optimization over Structured Inputs
LayoutPrompter: Awaken the Design Ability of Large Language Models
Estimation of Renyi Entropy and Mutual Information Based on Generalized Nearest-Neighbor Graphs
Training Over-parameterized Models with Non-decomposable Objectives
On Valid Optimal Assignment Kernels and Applications to Graph Classification
Accelerating Robotic Reinforcement Learning via Parameterized Action Primitives
Transfer Learning of Graph Neural Networks with Ego-graph Information Maximization
Efficient coding, channel capacity, and the emergence of retinal mosaics
Staggered Rollout Designs Enable Causal Inference Under Interference Without Network Knowledge
Constant-Expansion Suffices for Compressed Sensing with Generative Priors
Reinforcement Learning Policy as Macro Regulator Rather than Macro Placer
On Density Estimation with Diffusion Models
Two Time-scale Off-Policy TD Learning: Non-asymptotic Analysis over Markovian Samples
Adversarial Unlearning: Reducing Confidence Along Adversarial Directions
Achieving Rotational Invariance with Bessel-Convolutional Neural Networks
A Functional Extension of Semi-Structured Networks
HYDRA: Model Factorization Framework for Black-Box LLM Personalization
Fast Template Evaluation with Vector Quantization
Near-Optimal Lower Bounds For Convex Optimization For All Orders of Smoothness
Learning Invariants through Soft Unification
Reinforcement Learning with Automated Auxiliary Loss Search
Partially Observable SDE Models for Image Sequence Recognition Tasks
Towards Flexible Visual Relationship Segmentation
Point Based Value Iteration with Optimal Belief Compression for Dec-POMDPs
Instance-optimal PAC Algorithms for Contextual Bandits
Incremental and Decremental Support Vector Machine Learning
On the Identifiability of Sparse ICA without Assuming Non-Gaussianity
PointDAN: A Multi-Scale 3D Domain Adaption Network for Point Cloud Representation
Bayes-optimal learning of an extensive-width neural network from quadratically many samples
A Critical Evaluation of AI Feedback for Aligning Large Language Models
MomentumRNN: Integrating Momentum into Recurrent Neural Networks
Extracting Reward Functions from Diffusion Models
Information Bottleneck Optimization and Independent Component Extraction with Spiking Neurons
Certification of Distributional Individual Fairness
Tracking Time-varying Graphical Structure
Generative Category-level Object Pose Estimation via Diffusion Models
Exact Solutions of a Deep Linear Network
Hash Layers For Large Sparse Models
Safety Gymnasium: A Unified Safe Reinforcement Learning Benchmark
Homology Consistency Constrained Efficient Tuning for Vision-Language Models
Dual Averaging Method for Regularized Stochastic Learning and Online Optimization
Momentum Aggregation for Private Non-convex ERM
Delving into Out-of-Distribution Detection with Vision-Language Representations
An Application of Markov Random Fields to Range Sensing
Risk Aversion in Markov Decision Processes via Near Optimal Chernoff Bounds
Mobility-LLM: Learning Visiting Intentions and Travel Preference from Human Mobility Data with Large Language Models
Regret Minimization for Reinforcement Learning by Evaluating the Optimal Bias Function
Data-Efficient Structured Pruning via Submodular Optimization
FasterRisk: Fast and Accurate Interpretable Risk Scores
Intra Order-preserving Functions for Calibration of Multi-Class Neural Networks
Multi-way Interacting Regression via Factorization Machines
Finite Sample Convergence Rates of Zero-Order Stochastic Optimization Methods
Kalman Filter, Sensor Fusion, and Constrained Regression: Equivalences and Insights
One-Pass Distribution Sketch for Measuring Data Heterogeneity in Federated Learning
Decisions, Counterfactual Explanations and Strategic Behavior
RestoreAgent: Autonomous Image Restoration Agent via Multimodal Large Language Models
Generating High-Quality Explanations for Navigation in Partially-Revealed Environments
Self-Adaptively Learning to Demoiré from Focused and Defocused Image Pairs
Non-Local Recurrent Network for Image Restoration
Efficient methods for Gaussian Markov random fields under sparse linear constraints
On the Convergence Rate of Decomposable Submodular Function Minimization
Distributed Deep Learning In Open Collaborations
Exposing flaws of generative model evaluation metrics and their unfair treatment of diffusion models
Unsupervised Learning by Program Synthesis
Fairness Through Computationally-Bounded Awareness
SSL4EO-L: Datasets and Foundation Models for Landsat Imagery
Exploration via Elliptical Episodic Bonuses
Porcupine Neural Networks: Approximating Neural Network Landscapes
Independence Testing for Bounded Degree Bayesian Networks
Text Classification with Born's Rule
Improving Robustness using Generated Data
Safe LoRA: The Silver Lining of Reducing Safety Risks when Finetuning Large Language Models
Improving Elevator Performance Using Reinforcement Learning
Learning Discriminative Feature Transforms to Low Dimensions in Low Dimentions
Discontinuous Generalization in Large Committee Machines
Networks are Slacking Off: Understanding Generalization Problem in Image Deraining
Energy Guided Diffusion for Generating Neurally Exciting Images
Gaussian Process Dynamical Models
BACKSHIFT: Learning causal cyclic graphs from unknown shift interventions
Learning Deep Structured Multi-Scale Features using Attention-Gated CRFs for Contour Prediction
Flexible Diffusion Modeling of Long Videos
Adaptive Quantization and Density Estimation in Silicon
Convex Learning with Invariances
Evaluating language models as risk scores
Non-Linear PI Control Inspired by Biological Control Systems
Greedy Pruning with Group Lasso Provably Generalizes for Matrix Sensing
Accelerating Blockwise Parallel Language Models with Draft Refinement
Introduction to a System for Implementing Neural Net Connections on SIMD Architectures
Embedding Principle of Loss Landscape of Deep Neural Networks
Hardware Resilience Properties of Text-Guided Image Classifiers
Learning Influence among Interacting Markov Chains
Triple Eagle: Simple, Fast and Practical Budget-Feasible Mechanisms
Parametrizing Feature Sensitive Cell Formation in Linsker Networks in the Auditory System
Differential Privacy without Sensitivity
The Rescorla-Wagner Algorithm and Maximum Likelihood Estimation of Causal Parameters
A Neural Network for Feature Extraction
Nonlocal Neural Networks, Nonlocal Diffusion and Nonlocal Modeling
Unsupervised Learning of a Probabilistic Grammar for Object Detection and Parsing
Testing for Homogeneity with Kernel Fisher Discriminant Analysis
Bayesian Spike-Triggered Covariance Analysis
Why are some word orders more common than others? A uniform information density account
Diffusion Priors for Variational Likelihood Estimation and Image Denoising
Designing neurophysiology experiments to optimally constrain receptive field models along parametric submanifolds
Spectral Mixture Kernels for Multi-Output Gaussian Processes
TRS: Transferability Reduced Ensemble via Promoting Gradient Diversity and Model Smoothness
Any2Policy: Learning Visuomotor Policy with Any-Modality
BEVFusion: A Simple and Robust LiDAR-Camera Fusion Framework
Bias Correction of Learned Generative Models using Likelihood-Free Importance Weighting
Dynamic Features for Visual Speechreading: A Systematic Comparison
Shape and Time Distortion Loss for Training Deep Time Series Forecasting Models
End-to-End Meta-Bayesian Optimisation with Transformer Neural Processes
k*-Nearest Neighbors: From Global to Local
Distributed Saddle-Point Problems Under Data Similarity
The Generalized FITC Approximation
Advancing Tool-Augmented Large Language Models: Integrating Insights from Errors in Inference Trees
Biologically Inspired Dynamic Textures for Probing Motion Perception
Photorealistic Text-to-Image Diffusion Models with Deep Language Understanding
Understanding the Evolution of Linear Regions in Deep Reinforcement Learning
Generalized Correspondence-LDA Models (GC-LDA) for Identifying Functional Regions in the Brain
FairQueue: Rethinking Prompt Learning for Fair Text-to-Image Generation
Model-Based Offline Reinforcement Learning with Pessimism-Modulated Dynamics Belief
Beware of the Simulated DAG! Causal Discovery Benchmarks May Be Easy to Game