yusuke1997/dblp-id-title huggingface dataset:
LMC: Large Model Collaboration with Cross-assessment for Training-Free Open-Set Object Recognition
Prompt Certified Machine Unlearning with Randomized Gradient Smoothing and Quantization
Lexicon3D: Probing Visual Foundation Models for Complex 3D Scene Understanding
Path Integral Based Convolution and Pooling for Graph Neural Networks
Sub-Linear Memory: How to Make Performers SLiM
Active Inference in Concept Learning
Conditional independence testing under misspecified inductive biases
Planar Ultrametrics for Image Segmentation
Communication Efficient Distributed Training with Distributed Lion
Policy Optimization via Importance Sampling
A Retrospective on the Robot Air Hockey Challenge: Benchmarking Robust, Reliable, and Safe Learning Techniques for Real-world Robotics
Variational Graph Recurrent Neural Networks
Fast, Provable Algorithms for Isotonic Regression in all L_p-norms
Bayesian Model Selection Approach to Boundary Detection with Non-Local Priors
Waypoint Transformer: Reinforcement Learning via Supervised Learning with Intermediate Targets
Combinatorial Pure Exploration with Bottleneck Reward Function
Token Merging for Training-Free Semantic Binding in Text-to-Image Synthesis
Learning High-Density Regions for a Generalized Kolmogorov-Smirnov Test in High-Dimensional Data
Does Continual Learning Meet Compositionality? New Benchmarks and An Evaluation Framework
New Complexity-Theoretic Frontiers of Tractability for Neural Network Training
High-dimensional neural spike train analysis with generalized count linear dynamical systems
Acoustic-Imaging Computations by Echolocating Bats: Unification of Diversely-Represented Stimulus Features into Whole Images
Unveiling the Bias Impact on Symmetric Moral Consistency of Large Language Models
MeLLoC: Lossless Compression with High-order Mechanism Learning
Shaping Belief States with Generative Environment Models for RL
Towards Characterizing the First-order Query Complexity of Learning (Approximate) Nash Equilibria in Zero-sum Matrix Games
Uncertainty-Aware Learning for Zero-Shot Semantic Segmentation
The noise level in linear regression with dependent data
Infusing Self-Consistency into Density Functional Theory Hamiltonian Prediction via Deep Equilibrium Models
Navigating to the Best Policy in Markov Decision Processes
Towards Calibrated Model for Long-Tailed Visual Recognition from Prior Perspective
Kissing to Find a Match: Efficient Low-Rank Permutation Representation
Enhancing the Locality and Breaking the Memory Bottleneck of Transformer on Time Series Forecasting
Masked Two-channel Decoupling Framework for Incomplete Multi-view Weak Multi-label Learning
Third-order Smoothness Helps: Faster Stochastic Optimization Algorithms for Finding Local Minima
Learning Bipartite Graphs: Heavy Tails and Multiple Components
Multiplicative Updates for Classification by Mixture Models
L-CAD: Language-based Colorization with Any-level Descriptions using Diffusion Priors
Learning latent causal graphs via mixture oracles
Interpretable and Personalized Apprenticeship Scheduling: Learning Interpretable Scheduling Policies from Heterogeneous User Demonstrations
Without-Replacement Sampling for Stochastic Gradient Methods
Robust Reinforcement Learning via Adversarial training with Langevin Dynamics
Cornering Stationary and Restless Mixing Bandits with Remix-UCB
Learning Consistency-Aware Unsigned Distance Functions Progressively from Raw Point Clouds
Unsupervised Feature Selection for Accurate Recommendation of High-Dimensional Image Data
QATCH: Benchmarking SQL-centric tasks with Table Representation Learning Models on Your Data
Inference by Learning: Speeding-up Graphical Model Optimization via a Coarse-to-Fine Cascade of Pruning Classifiers
On Interaction Between Augmentations and Corruptions in Natural Corruption Robustness
The Kernel Trick for Distances
Spatial-Aware Feature Aggregation for Image based Cross-View Geo-Localization
CATER: Intellectual Property Protection on Text Generation APIs via Conditional Watermarks
Private (Stochastic) Non-Convex Optimization Revisited: Second-Order Stationary Points and Excess Risks
BasisFormer: Attention-based Time Series Forecasting with Learnable and Interpretable Basis
Dimensionality Reduction with Subspace Structure Preservation
Perceiving Complex Visual Scenes: An Oscillator Neural Network Model that Integrates Selective Attention, Perceptual Organization, and Invariant Recognition
Neural Characteristic Activation Analysis and Geometric Parameterization for ReLU Networks
Transformers as Game Players: Provable In-context Game-playing Capabilities of Pre-trained Models
Learning Temporal Dependencies in Connectionist Speech Recognition
Momentum Provably Improves Error Feedback!
Time-Warping Network: A Hybrid Framework for Speech Recognition
DISCO: Adversarial Defense with Local Implicit Functions
GOT: An Optimal Transport framework for Graph comparison
GRU-ODE-Bayes: Continuous Modeling of Sporadically-Observed Time Series
Probing Social Bias in Labor Market Text Generation by ChatGPT: A Masked Language Model Approach
A Probabilistic Framework for Multimodal Retrieval using Integrative Indian Buffet Process
On Optimal Interpolation in Linear Regression
Constraining a Bayesian Model of Human Visual Speed Perception
Labelling unlabelled videos from scratch with multi-modal self-supervision
Bridging Machine Learning and Logical Reasoning by Abductive Learning
Efficient Exploration in Continuous-time Model-based Reinforcement Learning
Learning Multimodal Behaviors from Scratch with Diffusion Policy Gradient
A Feasible Level Proximal Point Method for Nonconvex Sparse Constrained Optimization
On the Properties of Kullback-Leibler Divergence Between Multivariate Gaussian Distributions
Leveraging an ECG Beat Diffusion Model for Morphological Reconstruction from Indirect Signals
Active Learning Through a Covering Lens
A Unified Discretization Framework for Differential Equation Approach with Lyapunov Arguments for Convex Optimization
An Empirical Process Approach to the Union Bound: Practical Algorithms for Combinatorial and Linear Bandits
Neural Edit Operations for Biological Sequences
An Efficient Sequential Monte Carlo Algorithm for Coalescent Clustering
Gradient-based Discrete Sampling with Automatic Cyclical Scheduling
Stable Fitted Reinforcement Learning
Statistical Multicriteria Benchmarking via the GSD-Front
Contrastive Modules with Temporal Attention for Multi-Task Reinforcement Learning
ProteinInvBench: Benchmarking Protein Inverse Folding on Diverse Tasks, Models, and Metrics
Statistical Theory of Overtraining - Is Cross-Validation Asymptotically Effective?
Newton-Like Methods for Sparse Inverse Covariance Estimation
Adaptive Soft Weight Tying using Gaussian Mixtures
Development and Regeneration of Eye-Brain Maps: A Computational Model
GENO - GENeric Optimization for Classical Machine Learning
Theoretical Investigations and Practical Enhancements on Tail Task Risk Minimization in Meta Learning
Harmonic Grammars for Formal Languages
Personalizing Reinforcement Learning from Human Feedback with Variational Preference Learning
A Bandit Approach to Sequential Experimental Design with False Discovery Control
Memoized Online Variational Inference for Dirichlet Process Mixture Models
Noise Thresholds for Spectral Clustering
Effective Dimension Adaptive Sketching Methods for Faster Regularized Least-Squares Optimization
Logical Credal Networks
Second Order Bilinear Discriminant Analysis for single trial EEG analysis
Quantifying Common Support between Multiple Treatment Groups Using a Contrastive-VAE
Visually Grounded Video Reasoning in Selective Attention Memory
GCOMB: Learning Budget-constrained Combinatorial Algorithms over Billion-sized Graphs
Diffusion Model with Cross Attention as an Inductive Bias for Disentanglement
Multi-Modal Imitation Learning from Unstructured Demonstrations using Generative Adversarial Nets
DiffusionBlend: Learning 3D Image Prior through Position-aware Diffusion Score Blending for 3D Computed Tomography Reconstruction
SPEAR: Exact Gradient Inversion of Batches in Federated Learning
ProbTS: Benchmarking Point and Distributional Forecasting across Diverse Prediction Horizons
VLSI Implementations of Learning and Memory Systems
Fast Extra Gradient Methods for Smooth Structured Nonconvex-Nonconcave Minimax Problems
A General Framework for Robust G-Invariance in G-Equivariant Networks
Weakly-supervised Disentangling with Recurrent Transformations for 3D View Synthesis
Accumulative Poisoning Attacks on Real-time Data
A Low-Power Analog VLSI Visual Collision Detector
Understanding Few-Shot Learning: Measuring Task Relatedness and Adaptation Difficulty via Attributes
A Neurocomputer Board Based on the ANNA Neural Network Chip
Towards Neuron Attributions in Multi-Modal Large Language Models
Class-Aware Adversarial Transformers for Medical Image Segmentation
Stateful Strategic Regression
Generalized Model Selection for Unsupervised Learning in High Dimensions
Dopamine Induced Bistability Enhances Signal Processing in Spiny Neurons
How Does Adaptive Optimization Impact Local Neural Network Geometry?
Generative Time Series Forecasting with Diffusion, Denoise, and Disentanglement
An adaptive nearest neighbor rule for classification
Coupled Variational Bayes via Optimization Embedding
An Oscillatory Correlation Frame work for Computational Auditory Scene Analysis
Elastic Decision Transformer
RSKDD-Net: Random Sample-based Keypoint Detector and Descriptor
Enhanced Bilevel Optimization via Bregman Distance
Generalization Bounds for Graph Embedding Using Negative Sampling: Linear vs Hyperbolic
Cheap and Quick: Efficient Vision-Language Instruction Tuning for Large Language Models
Fast Neural Network Emulation of Dynamical Systems for Computer Animation
Information Theoretic Regret Bounds for Online Nonlinear Control
Generalisation of structural knowledge in the hippocampal-entorhinal system
Sparsistent Learning of Varying-coefficient Models with Structural Changes
Learning Cuts via Enumeration Oracles
Adversarial Style Mining for One-Shot Unsupervised Domain Adaptation
Language as a Cognitive Tool to Imagine Goals in Curiosity Driven Exploration
Fast Optimal Locally Private Mean Estimation via Random Projections
Stability of Graph Scattering Transforms
WONDERBREAD: A Benchmark for Evaluating Multimodal Foundation Models on Business Process Management Tasks
RIO: A Benchmark for Reasoning Intention-Oriented Objects in Open Environments
Explore In-Context Learning for 3D Point Cloud Understanding
Momentum-Based Variance Reduction in Non-Convex SGD
Unsupervised Semantic Correspondence Using Stable Diffusion
Direct Loss Minimization for Structured Prediction
Adversarial Representation Engineering: A General Model Editing Framework for Large Language Models
You Only Live Once: Single-Life Reinforcement Learning
Regression-tree Tuning in a Streaming Setting
muSSP: Efficient Min-cost Flow Algorithm for Multi-object Tracking
Learning discrete distributions: user vs item-level privacy
OpenGaussian: Towards Point-Level 3D Gaussian-based Open Vocabulary Understanding
SnapKV: LLM Knows What You are Looking for Before Generation
Characteristics of Harmful Text: Towards Rigorous Benchmarking of Language Models
Robustness Disparities in Face Detection
Attracting and Dispersing: A Simple Approach for Source-free Domain Adaptation
Benchmarking Out-of-Distribution Generalization Capabilities of DNN-based Encoding Models for the Ventral Visual Cortex
An Approximate Inference Approach to Temporal Optimization in Optimal Control
Implicit Surfaces with Globally Regularised and Compactly Supported Basis Functions
Optimal Algorithms for the Inhomogeneous Spiked Wigner Model
Locality-sensitive binary codes from shift-invariant kernels
Sampling-Decomposable Generative Adversarial Recommender
Demystifying Black-box Models with Symbolic Metamodels
Convolutional Kernel Networks
Flexible Attention-Based Multi-Policy Fusion for Efficient Deep Reinforcement Learning
An Analysis of SVD for Deep Rotation Estimation
A mathematical theory of cooperative communication
Bridging Explicit and Implicit Deep Generative Models via Neural Stein Estimators
Finite-Sample Convergence Rates for Q-Learning and Indirect Algorithms
Editing a classifier by rewriting its prediction rules
Query-based Temporal Fusion with Explicit Motion for 3D Object Detection
VidProM: A Million-scale Real Prompt-Gallery Dataset for Text-to-Video Diffusion Models
Proper losses for learning from partial labels
Jailbroken: How Does LLM Safety Training Fail?
A Comparative Study of a Modified Bumptree Neural Network with Radial Basis Function Networks and the Standard Multi Layer Perceptron
IconQA: A New Benchmark for Abstract Diagram Understanding and Visual Language Reasoning
Online Reinforcement Learning for Mixed Policy Scopes
A Motion-aware Spatio-temporal Graph for Video Salient Object Ranking
Towards Versatile Embodied Navigation
Convergence Rate Analysis of MAP Coordinate Minimization Algorithms
FedL2P: Federated Learning to Personalize
A Non-Asymptotic Moreau Envelope Theory for High-Dimensional Generalized Linear Models
Noise-tolerant fair classification
INDICT: Code Generation with Internal Dialogues of Critiques for Both Security and Helpfulness
MoGDE: Boosting Mobile Monocular 3D Object Detection with Ground Depth Estimation
Deep Self-Dissimilarities as Powerful Visual Fingerprints
Dynamically-Adaptive Winner-Take-All Networks
Multiple-Instance Active Learning
Language Grounding through Social Interactions and Curiosity-Driven Multi-Goal Learning
The continuous Bernoulli: fixing a pervasive error in variational autoencoders
Understanding the Differences in Foundation Models: Attention, State Space Models, and Recurrent Neural Networks
Large Scale Markov Decision Processes with Changing Rewards
Fast, Robust Adaptive Control by Learning only Forward Models
Towards Consistent Video Editing with Text-to-Image Diffusion Models
Accelerating Sparse Convolution with Column Vector-Wise Sparsity
Stochastic Optimization with Heavy-Tailed Noise via Accelerated Gradient Clipping
Revealing and Protecting Labels in Distributed Training
RL-based Stateful Neural Adaptive Sampling and Denoising for Real-Time Path Tracing
The Graph Pencil Method: Mapping Subgraph Densities to Stochastic Block Models
Model-based Adversarial Meta-Reinforcement Learning
Ranking Policy Decisions
AVeriTeC: A Dataset for Real-world Claim Verification with Evidence from the Web
Linguistic Collapse: Neural Collapse in (Large) Language Models
Certainty Equivalence is Efficient for Linear Quadratic Control
The Fixed Points of Off-Policy TD
Using the Future to Sort Out the Present: Rankprop and Multitask Learning for Medical Risk Evaluation
Revisiting Graph Contrastive Learning from the Perspective of Graph Spectrum
Gated Slot Attention for Efficient Linear-Time Sequence Modeling
MixACM: Mixup-Based Robustness Transfer via Distillation of Activated Channel Maps
Two-Layer Generalization Analysis for Ranking Using Rademacher Average
Contrastive Learning for Neural Topic Model
An Information-Theoretic Framework for Understanding Saccadic Eye Movements
TWIGMA: A dataset of AI-Generated Images with Metadata From Twitter
An Analog VLSI Chip for Finding Edges from Zero-crossings
Which graphical models are difficult to learn?
Evidential Stochastic Differential Equations for Time-Aware Sequential Recommendation
Computing Higher Order Derivatives of Matrix and Tensor Expressions
MCUNet: Tiny Deep Learning on IoT Devices
The Neural Costs of Optimal Control
Structured Voronoi Sampling
Global Rewards in Restless Multi-Armed Bandits
SpeechAlign: Aligning Speech Generation to Human Preferences
BAdam: A Memory Efficient Full Parameter Optimization Method for Large Language Models
Weighted Mutual Learning with Diversity-Driven Model Compression
Feature Selection for SVMs
Reshaped Wirtinger Flow for Solving Quadratic System of Equations
ProtoDiff: Learning to Learn Prototypical Networks by Task-Guided Diffusion
Precise Regret Bounds for Log-loss via a Truncated Bayesian Algorithm
Selective Generation for Controllable Language Models
Learning in Networks of Nondeterministic Adaptive Logic Elements
Compressed Regression
Infinite-Fidelity Coregionalization for Physical Simulation
HOI-Swap: Swapping Objects in Videos with Hand-Object Interaction Awareness
MagicBrush: A Manually Annotated Dataset for Instruction-Guided Image Editing
High-dimensional Additive Gaussian Processes under Monotonicity Constraints
Generalization for multiclass classification with overparameterized linear models
ExpandNets: Linear Over-parameterization to Train Compact Convolutional Networks
Training Connectionist Networks with Queries and Selective Sampling
Monte Carlo Methods for Maximum Margin Supervised Topic Models
Egocentric Planning for Scalable Embodied Task Achievement
S-PIFu: Integrating Parametric Human Models with PIFu for Single-view Clothed Human Reconstruction
Graph Contrastive Learning with Stable and Scalable Spectral Encoding
Teaching via Best-Case Counterexamples in the Learning-with-Equivalence-Queries Paradigm
The Strong Screening Rule for SLOPE
Score-based Source Separation with Applications to Digital Communication Signals
IMPACT: A Large-scale Integrated Multimodal Patent Analysis and Creation Dataset for Design Patents
QKFormer: Hierarchical Spiking Transformer using Q-K Attention
Biologically Inspired Mechanisms for Adversarial Robustness
TPU-KNN: K Nearest Neighbor Search at Peak FLOP/s
Measuring Robustness to Natural Distribution Shifts in Image Classification
Adjustable Robust Reinforcement Learning for Online 3D Bin Packing
Learning Representations for Hierarchies with Minimal Support
Functional Geometry Alignment and Localization of Brain Areas
Universal Style Transfer via Feature Transforms
Labeling Neural Representations with Inverse Recognition
On Integrated Clustering and Outlier Detection
Provably robust boosted decision stumps and trees against adversarial attacks
Single-Agent Policy Tree Search With Guarantees
An Information Theoretic Approach to Rule-Based Connectionist Expert Systems
SAPE: Spatially-Adaptive Progressive Encoding for Neural Optimization
History Filtering in Imperfect Information Games: Algorithms and Complexity
Disentangling Interpretable Factors with Supervised Independent Subspace Principal Component Analysis
Modeling Neural Population Spiking Activity with Gibbs Distributions
CNCA: Toward Customizable and Natural Generation of Adversarial Camouflage for Vehicle Detectors
Variational Bayesian Optimal Experimental Design
Learning from Bad Data via Generation
Tailoring: encoding inductive biases by optimizing unsupervised objectives at prediction time
Training a Quantum Neural Network
Real-Time Control of a Tokamak Plasma Using Neural Networks
Particle Filtering for Nonparametric Bayesian Matrix Factorization
Constraint Classification for Multiclass Classification and Ranking
A Topographic Product for the Optimization of Self-Organizing Feature Maps
Discrete Graph Hashing
Weakly Supervised 3D Open-vocabulary Segmentation
Improved Differential Privacy for SGD via Optimal Private Linear Operators on Adaptive Streams
Poisson-Minibatching for Gibbs Sampling with Convergence Rate Guarantees
Provably Efficient Online Hyperparameter Optimization with Population-Based Bandits
MIME: Mutual Information Minimization and Entropy Maximization for Bayesian Belief Propagation
Modeling Dyadic Data with Binary Latent Factors
Landmark-RxR: Solving Vision-and-Language Navigation with Fine-Grained Alignment Supervision
The Limits of Transfer Reinforcement Learning with Latent Low-rank Structure
Learning with Noise and Regularizers in Multilayer Neural Networks
Human Computation Requires and Enables a New Approach to Ethics
A Comparison between Neural Networks and other Statistical Techniques for Modeling the Relationship between Tobacco and Alcohol and Cancer
Learning 3D Equivariant Implicit Function with Patch-Level Pose-Invariant Representation
LoRA: A Logical Reasoning Augmented Dataset for Visual Question Answering
Stochastic Optimization with Variance Reduction for Infinite Datasets with Finite Sum Structure
DiscoveryWorld: A Virtual Environment for Developing and Evaluating Automated Scientific Discovery Agents
Global Distortions from Local Rewards: Neural Coding Strategies in Path-Integrating Neural Systems
The LASSO risk: asymptotic results and real world examples
Sparse Code Shrinkage: Denoising by Nonlinear Maximum Likelihood Estimation
Deterministic Symmetric Positive Semidefinite Matrix Completion
Unlabelled Sample Compression Schemes for Intersection-Closed Classes and Extremal Classes
Linearized Alternating Direction Method with Adaptive Penalty for Low-Rank Representation
Affine Structure From Sound
Supply-Side Equilibria in Recommender Systems
Mistake Bounds for Maximum Entropy Discrimination
Achieving Cross Modal Generalization with Multimodal Unified Representation
Unleashing the Denoising Capability of Diffusion Prior for Solving Inverse Problems
KAKURENBO: Adaptively Hiding Samples in Deep Neural Network Training
PROCAT: Product Catalogue Dataset for Implicit Clustering, Permutation Learning and Structure Prediction
NeuralPlane: An Efficiently Parallelizable Platform for Fixed-wing Aircraft Control with Reinforcement Learning
Graphical Models in Heavy-Tailed Markets
Differentially Private Linear Sketches: Efficient Implementations and Applications
HENASY: Learning to Assemble Scene-Entities for Interpretable Egocentric Video-Language Model
Calibrated Reliable Regression using Maximum Mean Discrepancy
Locality Preserving Projections
Implicit Probabilistic Integrators for ODEs
Dream the Impossible: Outlier Imagination with Diffusion Models
(More) Efficient Reinforcement Learning via Posterior Sampling
A Probabilistic Model for Learning Concatenative Morphology
EgoTracks: A Long-term Egocentric Visual Object Tracking Dataset
Optimal Black-Box Reductions Between Optimization Objectives
SA3DIP: Segment Any 3D Instance with Potential 3D Priors
Generalizable Relational Binding from Coarse-coded Distributed Representations
Subgroup Generalization and Fairness of Graph Neural Networks
Safe and Sparse Newton Method for Entropic-Regularized Optimal Transport
Grounding Spatio-Temporal Language with Transformers
Gaussian-process factor analysis for low-dimensional single-trial analysis of neural population activity
A Knowledge-Based Model of Geometry Learning
Contextual Decision-Making with Knapsacks Beyond the Worst Case
Thought Cloning: Learning to Think while Acting by Imitating Human Thinking
Sparse Random Feature Algorithm as Coordinate Descent in Hilbert Space
Predicting What You Already Know Helps: Provable Self-Supervised Learning
Learning Time-Varying Concepts
Score-Based Generative Models Detect Manifolds
Learning from Small Sample Sets by Combining Unsupervised Meta-Training with CNNs
Learning Halfspaces with the Zero-One Loss: Time-Accuracy Tradeoffs
UFC-BERT: Unifying Multi-Modal Controls for Conditional Image Synthesis
FFAM: Feature Factorization Activation Map for Explanation of 3D Detectors
Forward-Backward Latent State Inference for Hidden Continuous-Time semi-Markov Chains
Efficient learning of nonlinear prediction models with time-series privileged information
DOCTOR: A Simple Method for Detecting Misclassification Errors
A Bio-inspired Redundant Sensing Architecture
Sequential Bayesian Experimental Design with Variable Cost Structure
A PID Controller Approach for Adaptive Probability-dependent Gradient Decay in Model Calibration
When in Doubt: Neural Non-Parametric Uncertainty Quantification for Epidemic Forecasting
Conformal Classification with Equalized Coverage for Adaptively Selected Groups
Local Expectation Gradients for Black Box Variational Inference
Reasoning about Time and Knowledge in Neural Symbolic Learning Systems
A Differentiable Semantic Metric Approximation in Probabilistic Embedding for Cross-Modal Retrieval
A Charge-Based Parallel Analog Vector Quantizer
Memory Limited, Streaming PCA
Neural Network Analysis of Distributed Representations of Dynamical Sensory-Motor Transormations in the Leech
Robust Lasso with missing and grossly corrupted observations
Learning nonlinear level sets for dimensionality reduction in function approximation
Expert-level protocol translation for self-driving labs