yusuke1997/dblp-id-title huggingface dataset:
Test-Time Classifier Adjustment Module for Model-Agnostic Domain Generalization
Neuc-MDS: Non-Euclidean Multidimensional Scaling Through Bilinear Forms
Perfect Sampling from Pairwise Comparisons
Emergence of Topography and Complex Cell Properties from Natural Images using Extensions of ICA
Long-Form Video-Language Pre-Training with Multimodal Temporal Contrastive Learning
Bounding errors of Expectation-Propagation
Differentiable Structure Learning with Partial Orders
Provable Benefits of Actor-Critic Methods for Offline Reinforcement Learning
Robustness of Bayesian Neural Networks to Gradient-Based Attacks
Improved Output Coding for Classification Using Continuous Relaxation
A KL-LUCB algorithm for Large-Scale Crowdsourcing
Learning to Repair Software Vulnerabilities with Generative Adversarial Networks
Dynamic Bayesian Networks with Deterministic Latent Tables
Flocks of Stochastic Parrots: Differentially Private Prompt Learning for Large Language Models
Greedy Feature Construction
A Consolidated Cross-Validation Algorithm for Support Vector Machines via Data Reduction
Diminishing Returns Shape Constraints for Interpretability and Regularization
SheetCopilot: Bringing Software Productivity to the Next Level through Large Language Models
Regularizing Towards Permutation Invariance In Recurrent Models
Semi-Supervised Neural Architecture Search
Dynamic Tensor Product Regression
A Catalyst Framework for Minimax Optimization
Spectral Clustering of graphs with the Bethe Hessian
VideoMAE: Masked Autoencoders are Data-Efficient Learners for Self-Supervised Video Pre-Training
Quantification and the language of thought
MetaGAN: An Adversarial Approach to Few-Shot Learning
Learning Bounds for Domain Adaptation
Efficient Sampling for Gaussian Process Inference using Control Variables
Efficient Aggregated Kernel Tests using Incomplete $U$-statistics
Multi-Resolution Cascades for Multiclass Object Detection
Private Algorithms for Stochastic Saddle Points and Variational Inequalities: Beyond Euclidean Geometry
Gated Recurrent Convolution Neural Network for OCR
Combinatorial Group Testing with Selfish Agents
Score-based Generative Neural Networks for Large-Scale Optimal Transport
An Homotopy Algorithm for the Lasso with Online Observations
Automatic Curriculum Learning through Value Disagreement
Stability Bounds for Non-i.i.d. Processes
Searchlight Based Feature Extraction
Continuous Spatiotemporal Events Decoupling through Spike-based Bayesian Computation
Instructing Goal-Conditioned Reinforcement Learning Agents with Temporal Logic Objectives
Animate3D: Animating Any 3D Model with Multi-view Video Diffusion
DreamHuman: Animatable 3D Avatars from Text
Benchmarking Deep Inverse Models over time, and the Neural-Adjoint method
Colored Maximum Variance Unfolding
Discriminatively Trained Sparse Code Gradients for Contour Detection
Environment Generation for Zero-Shot Compositional Reinforcement Learning
Batch Active Learning at Scale
Archaeoscape: Bringing Aerial Laser Scanning Archaeology to the Deep Learning Era
HHD-GP: Incorporating Helmholtz-Hodge Decomposition into Gaussian Processes for Learning Dynamical Systems
On the Complexity of Learning Neural Networks
CliqueCNN: Deep Unsupervised Exemplar Learning
AC/DC: Alternating Compressed/DeCompressed Training of Deep Neural Networks
Manifold structure in graph embeddings
The Multi-Agent Behavior Dataset: Mouse Dyadic Social Interactions
TART: A plug-and-play Transformer module for task-agnostic reasoning
Right this way: Can VLMs Guide Us to See More to Answer Questions?
HyPoradise: An Open Baseline for Generative Speech Recognition with Large Language Models
Dialog without Dialog Data: Learning Visual Dialog Agents from VQA Data
On-the-fly Operation Batching in Dynamic Computation Graphs
The Complexity of Sparse Tensor PCA
Optimizing Multi-Class Spatio-Spectral Filters via Bayes Error Estimation for EEG Classification
MotionGS: Exploring Explicit Motion Guidance for Deformable 3D Gaussian Splatting
On Class Distributions Induced by Nearest Neighbor Graphs for Node Classification of Tabular Data
On the Role of Sparsity and DAG Constraints for Learning Linear DAGs
Maximal Cliques that Satisfy Hard Constraints with Application to Deformable Object Model Learning
Soft-Gated Warping-GAN for Pose-Guided Person Image Synthesis
Unconstrained Dynamic Regret via Sparse Coding
On Proper Learnability between Average- and Worst-case Robustness
Sample-Efficient Reinforcement Learning of Partially Observable Markov Games
Calibration of Shared Equilibria in General Sum Partially Observable Markov Games
Shift-Robust GNNs: Overcoming the Limitations of Localized Graph Training data
Non-Boltzmann Dynamics in Networks of Spiking Neurons
SHE: A Fast and Accurate Deep Neural Network for Encrypted Data
A Bandit Framework for Strategic Regression
Synbols: Probing Learning Algorithms with Synthetic Datasets
The Best of Both Worlds in Network Population Games: Reaching Consensus and Convergence to Equilibrium
Time Dependent Adaptive Neural Networks
Semi-Discrete Normalizing Flows through Differentiable Tessellation
Perturbing Hebbian Rules
Differentially Private Bayesian Inference for Exponential Families
Ordered Classes and Incomplete Examples in Classification
Enhance the Visual Representation via Discrete Adversarial Training
Towards Revealing the Mystery behind Chain of Thought: A Theoretical Perspective
The Capacity of the Kanerva Associative Memory is Exponential
Spectral Graph Pruning Against Over-Squashing and Over-Smoothing
ELIGN: Expectation Alignment as a Multi-Agent Intrinsic Reward
Deconvolving Feedback Loops in Recommender Systems
Training on Foveated Images Improves Robustness to Adversarial Attacks
Expectation Propagation in Gaussian Process Dynamical Systems
Fast Learning by Bounding Likelihoods in Sigmoid Type Belief Networks
Distinguishing discrete and continuous behavioral variability using warped autoregressive HMMs
MINT-1T: Scaling Open-Source Multimodal Data by 10x: A Multimodal Dataset with One Trillion Tokens
Newton Losses: Using Curvature Information for Learning with Differentiable Algorithms
A Second-Order Translation, Rotation and Scale Invariant Neural Network
CLeAR: Continual Learning on Algorithmic Reasoning for Human-like Intelligence
NeRV: Neural Representations for Videos
AMP: Automatically Finding Model Parallel Strategies with Heterogeneity Awareness
Fast deep reinforcement learning using online adjustments from the past
Action is in the Eye of the Beholder: Eye-gaze Driven Model for Spatio-Temporal Action Localization
Simple and Optimal Greedy Online Contention Resolution Schemes
Operation-Level Early Stopping for Robustifying Differentiable NAS
Bottleneck Structure in Learned Features: Low-Dimension vs Regularity Tradeoff
Learning Mean-Field Games
Unraveling the Gradient Descent Dynamics of Transformers
Implicit SVD for Graph Representation Learning
Branch & Learn for Recursively and Iteratively Solvable Problems in Predict+Optimize
Memory-Efficient Approximation Algorithms for Max-k-Cut and Correlation Clustering
Timeseries Anomaly Detection using Temporal Hierarchical One-Class Network
Scribbles for All: Benchmarking Scribble Supervised Segmentation Across Datasets
Video Object Segmentation with Adaptive Feature Bank and Uncertain-Region Refinement
Real-Valued Backpropagation is Unsuitable for Complex-Valued Neural Networks
Efficient Equivariant Transfer Learning from Pretrained Models
On the Implicit Bias of Linear Equivariant Steerable Networks
FFA-IR: Towards an Explainable and Reliable Medical Report Generation Benchmark
Column Selection via Adaptive Sampling
BERT Loses Patience: Fast and Robust Inference with Early Exit
Sketchy Moment Matching: Toward Fast and Provable Data Selection for Finetuning
ScenarioNet: Open-Source Platform for Large-Scale Traffic Scenario Simulation and Modeling
Towards a "Universal Translator" for Neural Dynamics at Single-Cell, Single-Spike Resolution
A Recurrent Model of the Interaction Between Prefrontal and Inferotemporal Cortex in Delay Tasks
Multi-Agent Domain Calibration with a Handful of Offline Data
Early stopping for kernel boosting algorithms: A general analysis with localized complexities
Pessimism for Offline Linear Contextual Bandits using $\ell_p$ Confidence Sets
Clebsch-Gordan Nets: a Fully Fourier Space Spherical Convolutional Neural Network
A Limitation of the PAC-Bayes Framework
DualDICE: Behavior-Agnostic Estimation of Discounted Stationary Distribution Corrections
Recurrent Neural Networks Can Learn to Implement Symbol-Sensitive Counting
Interaction Screening: Efficient and Sample-Optimal Learning of Ising Models
On the Value of Target Data in Transfer Learning
Towards practical differentially private causal graph discovery
Multi-modal Situated Reasoning in 3D Scenes
Optimal Decision Tree with Noisy Outcomes
Collaborative Ranking With 17 Parameters
Evaluating probabilities under high-dimensional latent variable models
Bellman Error Based Feature Generation using Random Projections on Sparse Spaces
Can Less be More? When Increasing-to-Balancing Label Noise Rates Considered Beneficial
Non-Linguistic Supervision for Contrastive Learning of Sentence Embeddings
Distributionally Adaptive Meta Reinforcement Learning
An Autoencoder Approach to Learning Bilingual Word Representations
Matrix Denoising with Doubly Heteroscedastic Noise: Fundamental Limits and Optimal Spectral Methods
The Ladder in Chaos: Improving Policy Learning by Harnessing the Parameter Evolving Path in A Low-dimensional Space
Make the U in UDA Matter: Invariant Consistency Learning for Unsupervised Domain Adaptation
YUSEG: Yolo and Unet is all you need for cell instance segmentation
Anytime-Competitive Reinforcement Learning with Policy Prior
Efficient Convex Relaxation for Transductive Support Vector Machine
Transformers learn to implement preconditioned gradient descent for in-context learning
Towards Safe Policy Improvement for Non-Stationary MDPs
Preference Learning of Latent Decision Utilities with a Human-like Model of Preferential Choice
PAC-Bayes Compression Bounds So Tight That They Can Explain Generalization
Real-Time Crowdsourcing of Health Data in a Low-Income Country: A Case Study of Human Data Supply on Malaria First-Line Treatment Policy Tracking in Nigeria
A Neural Network Model of 3-D Lightness Perception
APEBench: A Benchmark for Autoregressive Neural Emulators of PDEs
A New Alternating Direction Method for Linear Programming
Nonconvex Penalization Using Laplace Exponents and Concave Conjugates
Identifying Causal Effects via Context-specific Independence Relations
Provably and Practically Efficient Adversarial Imitation Learning with General Function Approximation
Object-Centric Learning for Real-World Videos by Predicting Temporal Feature Similarities
Extracting State Transition Dynamics from Multiple Spike Trains with Correlated Poisson HMM
Rethinking 3D Convolution in $\ell_p$-norm Space
Reverse Transition Kernel: A Flexible Framework to Accelerate Diffusion Inference
Policy Evaluation Using the Ω-Return
Why are Adaptive Methods Good for Attention Models?
Graph of Circuits with GNN for Exploring the Optimal Design Space
Multi-Armed Bandits with Metric Movement Costs
Concentrate Attention: Towards Domain-Generalizable Prompt Optimization for Language Models
Response Analysis of Neuronal Population with Synaptic Depression
DART: Articulated Hand Model with Diverse Accessories and Rich Textures
Operative dimensions in unconstrained connectivity of recurrent neural networks
Multi-Fidelity Best-Arm Identification
Black-box Backdoor Defense via Zero-shot Image Purification
Deep Shells: Unsupervised Shape Correspondence with Optimal Transport
An Application of Reversible-Jump MCMC to Multivariate Spherical Gaussian Mixtures
Rethinking Fourier Transform from A Basis Functions Perspective for Long-term Time Series Forecasting
On Occlusions in Video Action Detection: Benchmark Datasets And Training Recipes
Multi Time Scale World Models
Why Did This Model Forecast This Future? Information-Theoretic Saliency for Counterfactual Explanations of Probabilistic Regression Models
Deep Rao-Blackwellised Particle Filters for Time Series Forecasting
Implications of Model Indeterminacy for Explanations of Automated Decisions
On the Importance of Exploration for Generalization in Reinforcement Learning
Structured Prediction with Projection Oracles
Federated Reconstruction: Partially Local Federated Learning
General Munchausen Reinforcement Learning with Tsallis Kullback-Leibler Divergence
Adaptive Classification by Variational Kalman Filtering
Transduction with Matrix Completion: Three Birds with One Stone
Safe Reinforcement Learning via Curriculum Induction
Laughing Hyena Distillery: Extracting Compact Recurrences From Convolutions
Label Embedding Trees for Large Multi-Class Tasks
Stochastic Optimization for Large-scale Optimal Transport
Neural Symplectic Form: Learning Hamiltonian Equations on General Coordinate Systems
Last-Iterate Convergent Policy Gradient Primal-Dual Methods for Constrained MDPs
Parallel Backpropagation for Shared-Feature Visualization
Multimodal Generative Models for Scalable Weakly-Supervised Learning
Entropic Optimal Transport between Unbalanced Gaussian Measures has a Closed Form
A Principle for Unsupervised Hierarchical Decomposition of Visual Scenes
SBO-RNN: Reformulating Recurrent Neural Networks via Stochastic Bilevel Optimization
Robust Principal Component Analysis: Exact Recovery of Corrupted Low-Rank Matrices via Convex Optimization
Streaming Min-max Hypergraph Partitioning
rPPG-Toolbox: Deep Remote PPG Toolbox
Differentiable Random Partition Models
Censored Semi-Bandits: A Framework for Resource Allocation with Censored Feedback
Learning in Observable POMDPs, without Computationally Intractable Oracles
Few-Shot Audio-Visual Learning of Environment Acoustics
Meta-Gradient Reinforcement Learning
A Fair Classifier Using Kernel Density Estimation
RanDumb: Random Representations Outperform Online Continually Learned Representations
Deep Reinforcement Learning with Plasticity Injection
Modeling Short-term Noise Dependence of Spike Counts in Macaque Prefrontal Cortex
Scalable Intervention Target Estimation in Linear Models
Optimizing Automatic Differentiation with Deep Reinforcement Learning
PackQViT: Faster Sub-8-bit Vision Transformers via Full and Packed Quantization on the Mobile
Surfing: Iterative Optimization Over Incrementally Trained Deep Networks
Superposed Decoding: Multiple Generations from a Single Autoregressive Inference Pass
Theseus: A Library for Differentiable Nonlinear Optimization
Contrast, Attend and Diffuse to Decode High-Resolution Images from Brain Activities
Breaking the Activation Function Bottleneck through Adaptive Parameterization
A Unified Gradient-Descent/Clustering Architecture for Finite State Machine Induction
HAPI: A Large-scale Longitudinal Dataset of Commercial ML API Predictions
Beyond Unimodal: Generalising Neural Processes for Multimodal Uncertainty Estimation
Active Noise Canceling Using Analog Neuro-Chip with On-Chip Learning Capability
ShowMaker: Creating High-Fidelity 2D Human Video via Fine-Grained Diffusion Modeling
EF-BV: A Unified Theory of Error Feedback and Variance Reduction Mechanisms for Biased and Unbiased Compression in Distributed Optimization
Deeply Learning the Messages in Message Passing Inference
Assessing the Scalability of Biologically-Motivated Deep Learning Algorithms and Architectures
Can Simple Averaging Defeat Modern Watermarks?
M$^4$I: Multi-modal Models Membership Inference
Fair Sparse Regression with Clustering: An Invex Relaxation for a Combinatorial Problem
Mondrian Forests: Efficient Online Random Forests
Generalized Weighted Path Consistency for Mastering Atari Games
FLoRA: Federated Fine-Tuning Large Language Models with Heterogeneous Low-Rank Adaptations
Kaleido Diffusion: Improving Conditional Diffusion Models with Autoregressive Latent Modeling
Adaptive Regularization for Transductive Support Vector Machine
Renyi Differential Privacy of Propose-Test-Release and Applications to Private and Robust Machine Learning
Schrodinger Bridge Flow for Unpaired Data Translation
Solving Interpretable Kernel Dimensionality Reduction
Disentangled Contrastive Learning on Graphs
Sample Complexity of Asynchronous Q-Learning: Sharper Analysis and Variance Reduction
Measuring Generalization with Optimal Transport
CAST: Cross-Attention in Space and Time for Video Action Recognition
Apathetic or Empathetic? Evaluating LLMs' Emotional Alignments with Humans
Gradient-based Adaptive Markov Chain Monte Carlo
Parseval Regularization for Continual Reinforcement Learning
Agnostic Reinforcement Learning with Low-Rank MDPs and Rich Observations
Characterizing Datapoints via Second-Split Forgetting
Coarse-to-fine Animal Pose and Shape Estimation
Reinforcement Learning using Kernel-Based Stochastic Factorization
Row-clustering of a Point Process-valued Matrix
A Unified Generalization Analysis of Re-Weighting and Logit-Adjustment for Imbalanced Learning
Structured Machine Learning for Soft Classification with Smoothing Spline ANOVA and Stacked Tuning, Testing, and Evaluation
Learning Prototype Models for Tangent Distance
Fast Rates for Bandit PAC Multiclass Classification
Optimal Unsupervised Motor Learning Predicts the Internal Representation of Barn Owl Head Movements
Multilabel Structured Output Learning with Random Spanning Trees of Max-Margin Markov Networks
A Theoretical Understanding of Gradient Bias in Meta-Reinforcement Learning
Weight Normalization: A Simple Reparameterization to Accelerate Training of Deep Neural Networks
Latent Support Measure Machines for Bag-of-Words Data Classification
Dynamic allocation of limited memory resources in reinforcement learning
A Fast Post-Training Pruning Framework for Transformers
Bayesian Modeling and Classification of Neural Signals
Washing The Unwashable : On The (Im)possibility of Fairwashing Detection
Privacy-Preserving Q-Learning with Functional Noise in Continuous Spaces
Direct Importance Estimation with Model Selection and Its Application to Covariate Shift Adaptation
Spectral Learning of Dynamic Systems from Nonequilibrium Data
Probabilistic Matrix Factorization for Automated Machine Learning
Tight Bounds for Learning RUMs from Small Slates
Coda: An End-to-End Neural Program Decompiler
In What Ways Are Deep Neural Networks Invariant and How Should We Measure This?
Sim and Real: Better Together
Fast Tucker Rank Reduction for Non-Negative Tensors Using Mean-Field Approximation
Improving Online Rent-or-Buy Algorithms with Sequential Decision Making and ML Predictions
Neural Networks Fail to Learn Periodic Functions and How to Fix It
Rao-Blackwellised Particle Filtering via Data Augmentation
Fast Approximate Natural Gradient Descent in a Kronecker Factored Eigenbasis
Dynamics of Supervised Learning with Restricted Training Sets
'Ensemble' Boltzmann Units have Collective Computational Properties like those of Hopfield and Tank Neurons
The Convex Relaxation Barrier, Revisited: Tightened Single-Neuron Relaxations for Neural Network Verification
Joints in Random Forests
Sparse2Dense: Learning to Densify 3D Features for 3D Object Detection
Response Length Perception and Sequence Scheduling: An LLM-Empowered LLM Inference Pipeline
Screening Sinkhorn Algorithm for Regularized Optimal Transport
Robust Sequence Submodular Maximization
Qsparse-local-SGD: Distributed SGD with Quantization, Sparsification and Local Computations
Planning in Markov Decision Processes with Gap-Dependent Sample Complexity
Efficient Subgame Refinement for Extensive-form Games
Make-it-Real: Unleashing Large Multimodal Model for Painting 3D Objects with Realistic Materials
Meta-Learning through Hebbian Plasticity in Random Networks
Learning from Candidate Labeling Sets
Advances in Neural Information Processing Systems 28: Annual Conference on Neural Information Processing Systems 2015, December 7-12, 2015, Montreal, Quebec, Canada
Lightweight Frequency Masker for Cross-Domain Few-Shot Semantic Segmentation
Best Arm Identification with Fixed Budget: A Large Deviation Perspective
ABCFair: an Adaptable Benchmark approach for Comparing Fairness Methods
Importance Weighted Hierarchical Variational Inference
Learning Latent Process from High-Dimensional Event Sequences via Efficient Sampling
Estimating Robust Query Models with Convex Optimization
ContraGAN: Contrastive Learning for Conditional Image Generation
Exploring Molecular Pretraining Model at Scale
Scaled Gradients on Grassmann Manifolds for Matrix Completion
Learning to Generate Inversion-Resistant Model Explanations
Leveraging Separated World Model for Exploration in Visually Distracted Environments
Modular Gaussian Processes for Transfer Learning
Latent Planning via Expansive Tree Search
STARSS23: An Audio-Visual Dataset of Spatial Recordings of Real Scenes with Spatiotemporal Annotations of Sound Events
Multidimensional Scaling and Data Clustering
A Generative Model for Attractor Dynamics
Hierarchical Graph Transformer with Adaptive Node Sampling
BCDiff: Bidirectional Consistent Diffusion for Instantaneous Trajectory Prediction
Coresets for Regressions with Panel Data
Adaptive wavelet distillation from neural networks through interpretations
GV-Rep: A Large-Scale Dataset for Genetic Variant Representation Learning
Rational inference of relative preferences
A Unified Confidence Sequence for Generalized Linear Models, with Applications to Bandits
Pard: Permutation-Invariant Autoregressive Diffusion for Graph Generation
Enhancing Motion Deblurring in High-Speed Scenes with Spike Streams
No Filter: Cultural and Socioeconomic Diversity in Contrastive Vision-Language Models
Playing is believing: The role of beliefs in multi-agent learning
Information-theoretic generalization bounds for black-box learning algorithms
Adaptive Methods for Nonconvex Optimization
Differential Privacy Dynamics of Langevin Diffusion and Noisy Gradient Descent
Algebraic Information Geometry for Learning Machines with Singularities
Random Tessellation Forests
Constraints Based Convex Belief Propagation
A reinterpretation of the policy oscillation phenomenon in approximate policy iteration
Two Sides of The Same Coin: Bridging Deep Equilibrium Models and Neural ODEs via Homotopy Continuation
Large Language Models Are Semi-Parametric Reinforcement Learning Agents
Conditional Adapters: Parameter-efficient Transfer Learning with Fast Inference
VLSI Implementation of TInMANN
Bandit Learning with Implicit Feedback
Fairness without Demographics through Adversarially Reweighted Learning
Competition and Arbors in Ocular Dominance
Fast and Accurate Least-Mean-Squares Solvers
Modelling Relational Data using Bayesian Clustered Tensor Factorization
Wavelet Flow: Fast Training of High Resolution Normalizing Flows
Generalizablity of Memorization Neural Network
Minimal Variance Sampling in Stochastic Gradient Boosting
Learning Structure-Aware Representations of Dependent Types
Statistical Learning and Inverse Problems: A Stochastic Gradient Approach
Probing the Decision Boundaries of In-context Learning in Large Language Models
A simple but strong baseline for online continual learning: Repeated Augmented Rehearsal
MetaBox: A Benchmark Platform for Meta-Black-Box Optimization with Reinforcement Learning
Self-Healing Machine Learning: A Framework for Autonomous Adaptation in Real-World Environments
Generative Modelling of Stochastic Actions with Arbitrary Constraints in Reinforcement Learning
An Actor/Critic Algorithm that is Equivalent to Q-Learning
SPAE: Semantic Pyramid AutoEncoder for Multimodal Generation with Frozen LLMs
Hyper-Representations as Generative Models: Sampling Unseen Neural Network Weights
Learning Multiple Related Tasks using Latent Independent Component Analysis
An Information Theoretic Perspective on Conformal Prediction
Efficient and Robust Feature Extraction by Maximum Margin Criterion
Successor-Predecessor Intrinsic Exploration
Compressed Video Contrastive Learning
Approximation-Generalization Trade-offs under (Approximate) Group Equivariance
Waveform Driven Plasticity in BiFeO3 Memristive Devices: Model and Implementation
Understanding Programmatic Weak Supervision via Source-aware Influence Function
Lifelong Learning with Weighted Majority Votes
einspace: Searching for Neural Architectures from Fundamental Operations