yusuke1997/dblp-id-title huggingface dataset:
Towards Human-AI Complementarity with Prediction Sets
Ridge Regression and Provable Deterministic Ridge Leverage Score Sampling
Distributed Optimization for Overparameterized Problems: Achieving Optimal Dimension Independent Communication Complexity
Online Facility Location with Multiple Advice
Images that Sound: Composing Images and Sounds on a Single Canvas
The Hardness Analysis of Thompson Sampling for Combinatorial Semi-bandits with Greedy Oracle
Full-Distance Evasion of Pedestrian Detectors in the Physical World
Datasets for Online Controlled Experiments
An Oculo-Motor System with Multi-Chip Neuromorphic Analog VLSI Control
On Numerosity of Deep Neural Networks
UniFL: Improve Latent Diffusion Model via Unified Feedback Learning
Model-based Safe Deep Reinforcement Learning via a Constrained Proximal Policy Optimization Algorithm
SelfCodeAlign: Self-Alignment for Code Generation
Dual Defense: Enhancing Privacy and Mitigating Poisoning Attacks in Federated Learning
Landmark-Guided Subgoal Generation in Hierarchical Reinforcement Learning
Boosting Alignment for Post-Unlearning Text-to-Image Generative Models
Every View Counts: Cross-View Consistency in 3D Object Detection with Hybrid-Cylindrical-Spherical Voxelization
Make an Omelette with Breaking Eggs: Zero-Shot Learning for Novel Attribute Synthesis
Sub-sampling for Efficient Non-Parametric Bandit Exploration
Latent Template Induction with Gumbel-CRFs
Promises and Pitfalls of Threshold-based Auto-labeling
Sparse convolutional coding for neuronal assembly detection
A Comprehensive Analysis on the Learning Curve in Kernel Ridge Regression
Self-Supervised Alignment with Mutual Information: Learning to Follow Principles without Preference Labels
Consensus and Subjectivity of Skin Tone Annotation for ML Fairness
SiT Dataset: Socially Interactive Pedestrian Trajectory Dataset for Social Navigation Robots
Minimax Classification with 0-1 Loss and Performance Guarantees
Linear Complementarity for Regularized Policy Evaluation and Improvement
DDXPlus: A New Dataset For Automatic Medical Diagnosis
CSMeD: Bridging the Dataset Gap in Automated Citation Screening for Systematic Literature Reviews
Transient Signal Detection with Neural Networks: The Search for the Desired Signal
Faster width-dependent algorithm for mixed packing and covering LPs
Kernel quadrature with DPPs
Localized Data Fusion for Kernel k-Means Clustering with Application to Cancer Biology
Certifying Robustness to Programmable Data Bias in Decision Trees
Rethinking LLM Memorization through the Lens of Adversarial Compression
The Laplacian PDF Distance: A Cost Function for Clustering in a Kernel Feature Space
Tight convex relaxations for sparse matrix factorization
OPEN: Orthogonal Propagation with Ego-Network Modeling
Sharpness-Aware Minimization Activates the Interactive Teaching's Understanding and Optimization
Learning Contrastive Embedding in Low-Dimensional Space
Time-Conditioned Dances with Simplicial Complexes: Zigzag Filtration Curve based Supra-Hodge Convolution Networks for Time-series Forecasting
CADet: Fully Self-Supervised Out-Of-Distribution Detection With Contrastive Learning
GPT-ST: Generative Pre-Training of Spatio-Temporal Graph Neural Networks
SpreadsheetBench: Towards Challenging Real World Spreadsheet Manipulation
The Pitfalls of Simplicity Bias in Neural Networks
Ensembling geophysical models with Bayesian Neural Networks
Generalization Bounds with Minimal Dependency on Hypothesis Class via Distributionally Robust Optimization
Assessing Social and Intersectional Biases in Contextualized Word Representations
Robust Models are less Over-Confident
SWT-Bench: Testing and Validating Real-World Bug-Fixes with Code Agents
Freya PAGE: First Optimal Time Complexity for Large-Scale Nonconvex Finite-Sum Optimization with Heterogeneous Asynchronous Computations
Enhancing Consistency-Based Image Generation via Adversarialy-Trained Classification and Energy-Based Discrimination
Support Vector Novelty Detection Applied to Jet Engine Vibration Spectra
Adaptive Primal-Dual Splitting Methods for Statistical Learning and Image Processing
A Contrastive Learning Approach for Training Variational Autoencoder Priors
A Brain-Machine Interface Operating with a Real-Time Spiking Neural Network Control Algorithm
The surprising efficiency of framing geo-spatial time series forecasting as a video prediction task - Insights from the IARAI Traffic4cast Competition at NeurIPS 2019
No Free Lunch Theorem and Black-Box Complexity Analysis for Adversarial Optimisation
Adversarial Training for Graph Neural Networks: Pitfalls, Solutions, and New Directions
Coordinate Linear Variance Reduction for Generalized Linear Programming
Variational Multi-scale Representation for Estimating Uncertainty in 3D Gaussian Splatting
Structured Multi-Track Accompaniment Arrangement via Style Prior Modelling
UniBias: Unveiling and Mitigating LLM Bias through Internal Attention and FFN Manipulation
Learning Segmentation by Random Walks
Universal Online Learning with Gradient Variations: A Multi-layer Online Ensemble Approach
Discriminative Direction for Kernel Classifiers
A Full-duplex Speech Dialogue Scheme Based On Large Language Model
The Neurothermostat: Predictive Optimal Control of Residential Heating Systems
Neural Architecture Generator Optimization
Associative Memory in a Network of 'Biological' Neurons
Analog Circuits for Constrained Optimization
Near Instance-Optimal PAC Reinforcement Learning for Deterministic MDPs
Effects of Firing Synchrony on Signal Propagation in Layered Networks
Chanakya: Learning Runtime Decisions for Adaptive Real-Time Perception
Robust Gaussian Processes via Relevance Pursuit
Dataflow Architectures: Flexible Platforms for Neural Network Simulation
Trajectory-Based Short-Sighted Probabilistic Planning
CogView: Mastering Text-to-Image Generation via Transformers
Meta-learning from Tasks with Heterogeneous Attribute Spaces
q-means: A quantum algorithm for unsupervised machine learning
A Self-Learning Neural Network
On Graph Reconstruction via Empirical Risk Minimization: Fast Learning Rates and Scalability
Streaming Variational Bayes
Exploratory Retrieval-Augmented Planning For Continual Embodied Instruction Following
Federated Graph Learning for Cross-Domain Recommendation
Scalable Structure Learning of Continuous-Time Bayesian Networks from Incomplete Data
A Rotated Hyperbolic Wrapped Normal Distribution for Hierarchical Representation Learning
Intervention and Conditioning in Causal Bayesian Networks
Image Reconstruction Via Autoencoding Sequential Deep Image Prior
Learning Restricted Boltzmann Machines with Sparse Latent Variables
Learning Macroscopic Dynamics from Partial Microscopic Observations
Refusal in Language Models Is Mediated by a Single Direction
Generalization Performance in PARSEC - A Structured Connectionist Parsing Architecture
Learning Unambiguous Reduced Sequence Descriptions
Learning Conditional Deformable Templates with Convolutional Networks
A generative nonparametric Bayesian model for whole genomes
Regret Bounds without Lipschitz Continuity: Online Learning with Relative-Lipschitz Losses
DinoSR: Self-Distillation and Online Clustering for Self-supervised Speech Representation Learning
When does Contrastive Learning Preserve Adversarial Robustness from Pretraining to Finetuning?
Trading off Mistakes and Don't-Know Predictions
Multiclass Learning Approaches: A Theoretical Comparison with Implications
Deep Wiener Deconvolution: Wiener Meets Deep Learning for Image Deblurring
Recognition-Based Segmentation of On-Line Cursive Handwriting
Neural Lyapunov Control for Discrete-Time Systems
A Reduction-based Framework for Sequential Decision Making with Delayed Feedback
Analog VLSI Implementation of Gradient Descent
Fast Optimal Transport through Sliced Generalized Wasserstein Geodesics
BackTime: Backdoor Attacks on Multivariate Time Series Forecasting
On Efficient Heuristic Ranking of Hypotheses
Graph Normalizing Flows
MARPLE: A Benchmark for Long-Horizon Inference
Perturbation Towards Easy Samples Improves Targeted Adversarial Transferability
Learning with Recursive Perceptual Representations
CrypTen: Secure Multi-Party Computation Meets Machine Learning
Liberty or Depth: Deep Bayesian Neural Nets Do Not Need Complex Weight Posterior Approximations
Learning Eigenvectors for Free
Chain of Thought Imitation with Procedure Cloning
Measuring Goal-Directedness
Rotating Features for Object Discovery
A General Framework for Equivariant Neural Networks on Reductive Lie Groups
Vicinal Risk Minimization
Controlled Text Generation as Continuous Optimization with Multiple Constraints
SpGesture: Source-Free Domain-adaptive sEMG-based Gesture Recognition with Jaccard Attentive Spiking Neural Network
Revisiting Neural Scaling Laws in Language and Vision
Factorized Diffusion Architectures for Unsupervised Image Generation and Segmentation
Can Temporal-Difference and Q-Learning Learn Representation? A Mean-Field Theory
Linear-time Algorithms for Pairwise Statistical Problems
Towards Understanding Extrapolation: a Causal Lens
Dynamic visual attention: searching for coding length increments
Principles of Risk Minimization for Learning Theory
Neural Network Star Pattern Recognition for Spacecraft Attitude Determination and Control
Rethinking Imbalance in Image Super-Resolution for Efficient Inference
Natural Actor-Critic for Robust Reinforcement Learning with Function Approximation
Spike-Train Level Backpropagation for Training Deep Recurrent Spiking Neural Networks
3D Steerable CNNs: Learning Rotationally Equivariant Features in Volumetric Data
Robust Spectral Detection of Global Structures in the Data by Learning a Regularization
Goal-Conditioned Predictive Coding for Offline Reinforcement Learning
The First International Competition in Machine Reconnaissance Blind Chess
Planning from Pixels in Environments with Combinatorially Hard Search Spaces
Mobile-Agent-v2: Mobile Device Operation Assistant with Effective Navigation via Multi-Agent Collaboration
Machine Learning Estimation of Heterogeneous Treatment Effects with Instruments
Equivariant Neural Simulators for Stochastic Spatiotemporal Dynamics
Memory safe computations with XLA compiler
Stochastic Optimization for Performative Prediction
TreeMoCo: Contrastive Neuron Morphology Representation Learning
Generating Images with Multimodal Language Models
A Fractional Graph Laplacian Approach to Oversmoothing
Online Learning in Markov Decision Processes with Adversarially Chosen Transition Probability Distributions
Fixed-Distance Hamiltonian Monte Carlo
Restart Sampling for Improving Generative Processes
Poisson Variational Autoencoder
CLDA: Contrastive Learning for Semi-Supervised Domain Adaptation
Cost-Sensitive Exploration in Bayesian Reinforcement Learning
Unsupervised Structure Discovery for Semantic Analysis of Audio
Distributed Representations of Words and Phrases and their Compositionality
How SVMs can estimate quantiles and the median
Rethinking Decoders for Transformer-based Semantic Segmentation: A Compression Perspective
Using Embeddings to Correct for Unobserved Confounding in Networks
FourierGNN: Rethinking Multivariate Time Series Forecasting from a Pure Graph Perspective
Hierarchical classification at multiple operating points
End-to-End Weak Supervision
Local Differential Privacy for Regret Minimization in Reinforcement Learning
Contrastive Lift: 3D Object Instance Segmentation by Slow-Fast Contrastive Fusion
Fundamental Limitations of Spectral Clustering
Patterns of damage in neural networks: The effects of lesion area, shape and number
Speedup Matrix Completion with Side Information: Application to Multi-Label Learning
Training Linear Finite-State Machines
Algorithmic Linearly Constrained Gaussian Processes
Slice-based Learning: A Programming Model for Residual Learning in Critical Data Slices
Scalable kernels for graphs with continuous attributes
Adaptive Path-Integral Autoencoders: Representation Learning and Planning for Dynamical Systems
Contrastive Neural Ratio Estimation
Perspective Transformer Nets: Learning Single-View 3D Object Reconstruction without 3D Supervision
Self-Calibrating Conformal Prediction
Rel3D: A Minimally Contrastive Benchmark for Grounding Spatial Relations in 3D
Collaborative Recurrent Autoencoder: Recommend while Learning to Fill in the Blanks
MVP-N: A Dataset and Benchmark for Real-World Multi-View Object Classification
Policy Aggregation
Complementary Benefits of Contrastive Learning and Self-Training Under Distribution Shift
Funnel-Transformer: Filtering out Sequential Redundancy for Efficient Language Processing
Preference Based Adaptation for Learning Objectives
Neuronal Adaptation for Sampling-Based Probabilistic Inference in Perceptual Bistability
Diffusion-based Layer-wise Semantic Reconstruction for Unsupervised Out-of-Distribution Detection
A Probabilistic Algorithm Integrating Source Localization and Noise Suppression of MEG and EEG data
Meta-Exploiting Frequency Prior for Cross-Domain Few-Shot Learning
Learning to Assimilate in Chaotic Dynamical Systems
The Effect of Catecholamines on Performance: From Unit to System Behavior
LSTD with Random Projections
What Makes CLIP More Robust to Long-Tailed Pre-Training Data? A Controlled Study for Transferable Insights
Robust Sub-Gaussian Principal Component Analysis and Width-Independent Schatten Packing
Compressive Feature Learning
GAPX: Generalized Autoregressive Paraphrase-Identification X
Equality of Opportunity in Classification: A Causal Approach
Meaningful Learning: Enhancing Abstract Reasoning in Large Language Models via Generic Fact Guidance
Learning as MAP Inference in Discrete Graphical Models
Differentially-Private Federated Linear Bandits
Using Tarjan's Red Rule for Fast Dependency Tree Construction
ARKitScenes: A Diverse Real-World Dataset For 3D Indoor Scene Understanding Using Mobile RGB-D Data
RainNet: A Large-Scale Imagery Dataset and Benchmark for Spatial Precipitation Downscaling
Conservative Offline Distributional Reinforcement Learning
VaiPhy: a Variational Inference Based Algorithm for Phylogeny
General Detection-based Text Line Recognition
This Looks Like That: Deep Learning for Interpretable Image Recognition
Incremental Gaussian Processes
Achievable distributional robustness when the robust risk is only partially identified
Catching heuristics are optimal control policies
Label Noise SGD Provably Prefers Flat Global Minimizers
Revisiting 3D Object Detection From an Egocentric Perspective
Relational Proxies: Emergent Relationships as Fine-Grained Discriminators
Convolutional Networks on Graphs for Learning Molecular Fingerprints
Approximating Hierarchical MV-sets for Hierarchical Clustering
NPCL: Neural Processes for Uncertainty-Aware Continual Learning
Active Learning and Best-Response Dynamics
CigTime: Corrective Instruction Generation Through Inverse Motion Editing
DeepHeartBeat: Latent trajectory learning of cardiac cycles using cardiac ultrasounds
Asymptotics of Alpha-Divergence Variational Inference Algorithms with Exponential Families
Multi-dynamic Bayesian Networks
Shifts: A Dataset of Real Distributional Shift Across Multiple Large-Scale Tasks
Overlaying classifiers: a practical approach for optimal ranking
Phase Diagram and Storage Capacity of Sequence-Storing Neural Networks
Flow: Per-instance Personalized Federated Learning
Rethinking Generalization in Few-Shot Classification
A joint maximum-entropy model for binary neural population patterns and continuous signals
BIOSCAN-5M: A Multimodal Dataset for Insect Biodiversity
Provably Adversarially Robust Detection of Out-of-Distribution Data (Almost) for Free
Divergence Frontiers for Generative Models: Sample Complexity, Quantization Effects, and Frontier Integrals
Debias Coarsely, Sample Conditionally: Statistical Downscaling through Optimal Transport and Probabilistic Diffusion Models
Diversity can be Transferred: Output Diversification for White- and Black-box Attacks
MAP Inference for Bayesian Inverse Reinforcement Learning
Self-regulation Mechanism of Temporally Asymmetric Hebbian Plasticity
Contextual Active Model Selection
Sample Complexity for Learning Recurrent Perceptron Mappings
Recaptured Raw Screen Image and Video Demoiréing via Channel and Spatial Modulations
Geometric entropy minimization (GEM) for anomaly detection and localization
Incremental Variational Sparse Gaussian Process Regression
Computing Nash Equilibria in Generalized Interdependent Security Games
Chain-of-Thought Prompting Elicits Reasoning in Large Language Models
Solving Zero-Sum Markov Games with Continuous State via Spectral Dynamic Embedding
Tight Certificates of Adversarial Robustness for Randomly Smoothed Classifiers
Polynomial Semantic Indexing
Learning a Neuron by a Shallow ReLU Network: Dynamics and Implicit Bias for Correlated Inputs
Online Knapsack with Frequency Predictions
Protein contact prediction from amino acid co-evolution using convolutional networks for graph-valued images
EF21: A New, Simpler, Theoretically Better, and Practically Faster Error Feedback
Privacy Auditing with One (1) Training Run
Use perturbations when learning from explanations
Minimax Theory for High-dimensional Gaussian Mixtures with Sparse Mean Separation
Implementation Issues in the Fourier Transform Algorithm
Long-Tailed Classification by Keeping the Good and Removing the Bad Momentum Causal Effect
Reconstructing Stimulus-Driven Neural Networks from Spike Times
Bridging the Gap between Sample-based and One-shot Neural Architecture Search with BONAS
Amortized Fourier Neural Operators
On Algorithms for Sparse Multi-factor NMF
Efficient Optimization for Sparse Gaussian Process Regression
Towards Learning Group-Equivariant Features for Domain Adaptive 3D Detection
Scaling Neural Tangent Kernels via Sketching and Random Features
Associative memory in realistic neuronal networks
M$^3$GPT: An Advanced Multimodal, Multitask Framework for Motion Comprehension and Generation
Improving Temporal Link Prediction via Temporal Walk Matrix Projection
Global Convergence and Variance Reduction for a Class of Nonconvex-Nonconcave Minimax Problems
Neural collapse vs. low-rank bias: Is deep neural collapse really optimal?
Communication Acceleration of Local Gradient Methods via an Accelerated Primal-Dual Algorithm with an Inexact Prox
Anytime-Valid Inference For Multinomial Count Data
Graphical Gaussian Vector for Image Categorization
Architecture Matters: Uncovering Implicit Mechanisms in Graph Contrastive Learning
Memorability of Image Regions
Towards Heterogeneous Long-tailed Learning: Benchmarking, Metrics, and Toolbox
TRIAGE: Characterizing and auditing training data for improved regression
Boosting Generalization in Parametric PDE Neural Solvers through Adaptive Conditioning
Online Optimization in X-Armed Bandits
Multi-task Vector Field Learning
Neural Networks Structured for Control Application to Aircraft Landing
Deep Extended Hazard Models for Survival Analysis
Combinatorial Optimization with Policy Adaptation using Latent Space Search
On Line Estimation of Optimal Control Sequences: HJB Estimators
A2: Efficient Automated Attacker for Boosting Adversarial Training
Acceleration via Symplectic Discretization of High-Resolution Differential Equations
AutoPrivacy: Automated Layer-wise Parameter Selection for Secure Neural Network Inference
Sym-NCO: Leveraging Symmetricity for Neural Combinatorial Optimization
Optimal testing using combined test statistics across independent studies
SMPL: Simulated Industrial Manufacturing and Process Control Learning Environments
Flatten Anything: Unsupervised Neural Surface Parameterization
Submodular Multi-Label Learning
Scaling Up Exact Neural Network Compression by ReLU Stability
Network Structuring and Training Using Rule-Based Knowledge
Scaling Multimodal Pre-Training via Cross-Modality Gradient Harmonization
Doubly Robust Augmented Transfer for Meta-Reinforcement Learning
Bundle Methods for Machine Learning
Zero-Shot Transfer with Deictic Object-Oriented Representation in Reinforcement Learning
COLA: Decentralized Linear Learning
T2V-Turbo: Breaking the Quality Bottleneck of Video Consistency Model with Mixed Reward Feedback
Distributed Online Convex Optimization with Compressed Communication
4D Unsupervised Object Discovery
Learning and Transferring Sparse Contextual Bigrams with Linear Transformers
Beyond Myopia: Learning from Positive and Unlabeled Data through Holistic Predictive Trends
Aligning Vision Models with Human Aesthetics in Retrieval: Benchmarks and Algorithms
Integrating Locally Learned Causal Structures with Overlapping Variables
ToolkenGPT: Augmenting Frozen Language Models with Massive Tools via Tool Embeddings
Separation of Music Signals by Harmonic Structure Modeling
Online allocation and homogeneous partitioning for piecewise constant mean-approximation
Teaching Machines to Describe Images with Natural Language Feedback
Learning Domain Invariant Representations in Goal-conditioned Block MDPs
Learning Repeatable Speech Embeddings Using An Intra-class Correlation Regularizer
What Matters in Graph Class Incremental Learning? An Information Preservation Perspective
Improving Gloss-free Sign Language Translation by Reducing Representation Density
Tree in Tree: from Decision Trees to Decision Graphs
Foreground Clustering for Joint Segmentation and Localization in Videos and Images
A Bayesian Model for Simultaneous Image Clustering, Annotation and Object Segmentation
Decomposition Bounds for Marginal MAP
Log-Linear-Time Gaussian Processes Using Binary Tree Kernels
On Elimination Strategies for Bandit Fixed-Confidence Identification
A Framework for Testing Identifiability of Bayesian Models of Perception
LLC: Accurate, Multi-purpose Learnt Low-dimensional Binary Codes
Generalization Bounds for Meta-Learning via PAC-Bayes and Uniform Stability
Adaptive Ensemble Q-learning: Minimizing Estimation Bias via Error Feedback
Causal Discovery in Semi-Stationary Time Series
FORB: A Flat Object Retrieval Benchmark for Universal Image Embedding
Adaptive Gradient Quantization for Data-Parallel SGD
Attention Temperature Matters in ViT-Based Cross-Domain Few-Shot Learning
Volume Feature Rendering for Fast Neural Radiance Field Reconstruction
Simple and Scalable Predictive Uncertainty Estimation using Deep Ensembles
Evaluating Numerical Reasoning in Text-to-Image Models
Fast Conditional Mixing of MCMC Algorithms for Non-log-concave Distributions
Multi-View Representation Learning via Total Correlation Objective
On Socially Fair Low-Rank Approximation and Column Subset Selection
Dual Mean-Teacher: An Unbiased Semi-Supervised Framework for Audio-Visual Source Localization
Transductive Learning is Compact
Analysis of Short Term Memories for Neural Networks
An interior-point stochastic approximation method and an L1-regularized delta rule
Referring Transformer: A One-step Approach to Multi-task Visual Grounding
Learning Control Under Extreme Uncertainty
Streaming Bayes GFlowNets
Using Partial Monotonicity in Submodular Maximization
Self-organization of Hebbian Synapses in Hippocampal Neurons
Reliable Graph Neural Networks via Robust Aggregation
Half-Lives of EigenFlows for Spectral Clustering
Vivid-ZOO: Multi-View Video Generation with Diffusion Model
Towards Scalable Bayesian Learning of Causal DAGs
Wide Feedforward or Recurrent Neural Networks of Any Architecture are Gaussian Processes
Efficient Multi-task LLM Quantization and Serving for Multiple LoRA Adapters
ELDEN: Exploration via Local Dependencies
EIGNN: Efficient Infinite-Depth Graph Neural Networks
Dual Risk Minimization: Towards Next-Level Robustness in Fine-tuning Zero-Shot Models
Faster Repeated Evasion Attacks in Tree Ensembles
Learning of Discrete Graphical Models with Neural Networks
A Mean Field Algorithm for Bayes Learning in Large Feed-forward Neural Networks
Copula Bayesian Networks
Theory and Dynamics of Perceptual Bistability
Clustering Sparse Graphs
A Mixture Of Surprises for Unsupervised Reinforcement Learning
Selectivity and Metaplasticity in a Unified Calcium-Dependent Model
SARAD: Spatial Association-Aware Anomaly Detection and Diagnosis for Multivariate Time Series
Local Convergence of Gradient Methods for Min-Max Games: Partial Curvature Generically Suffices
Text Alignment Is An Efficient Unified Model for Massive NLP Tasks
De-Anonymizing Text by Fingerprinting Language Generation