yusuke1997/dblp-id-title huggingface dataset:
Neural Conservation Laws: A Divergence-Free Perspective
Uncovering Neural Scaling Laws in Molecular Representation Learning
Fast and Furious Learning in Zero-Sum Games: Vanishing Regret with Non-Vanishing Step Sizes
Using Aperiodic Reinforcement for Directed Self-Organization During Development
Fisher Scoring and a Mixture of Modes Approach for Approximate Inference and Learning in Nonlinear State Space Models
GVKF: Gaussian Voxel Kernel Functions for Highly Efficient Surface Reconstruction in Open Scenes
Multi-Electrode Spike Sorting by Clustering Transfer Functions
SoundSpaces 2.0: A Simulation Platform for Visual-Acoustic Learning
Adversarial Scene Editing: Automatic Object Removal from Weak Supervision
Improving model calibration with accuracy versus uncertainty optimization
LISA: Layerwise Importance Sampling for Memory-Efficient Large Language Model Fine-Tuning
Breaking SVM Complexity with Cross-Training
Insights from Machine Learning Applied to Human Visual Classification
SegVol: Universal and Interactive Volumetric Medical Image Segmentation
Near-Optimality of Contrastive Divergence Algorithms
Staying up to Date with Online Content Changes Using Reinforcement Learning for Scheduling
Latent Bandits Revisited
Off-Policy Evaluation with Deficient Support Using Side Information
Myriad: a real-world testbed to bridge trajectory optimization and deep learning
Circuit as Set of Points
Learning with Explanation Constraints
Feature Learning for Interpretable, Performant Decision Trees
Spoken Language Understanding on the Edge
Finer Metagenomic Reconstruction via Biodiversity Optimization
Patch Diffusion: Faster and More Data-Efficient Training of Diffusion Models
Latent Alignment and Variational Attention
Reinforcement Learning for Solving the Vehicle Routing Problem
Semantic Kernel Forests from Multiple Taxonomies
Humor in AI: Massive Scale Crowd-Sourced Preferences and Benchmarks for Cartoon Captioning
CryoSPIN: Improving Ab-Initio Cryo-EM Reconstruction with Semi-Amortized Pose Inference
Fast Approximation of the Sliced-Wasserstein Distance Using Concentration of Random Projections
Unsupervised Transcription of Piano Music
Premise Selection for Theorem Proving by Deep Graph Embedding
When is an Embedding Model More Promising than Another?
On Giant's Shoulders: Effortless Weak to Strong by Dynamic Logits Fusion
CUAD: An Expert-Annotated NLP Dataset for Legal Contract Review
Linear Operator for Object Recognition
Bifröst: 3D-Aware Image Compositing with Language Instructions
On clustering network-valued data
GEX: A flexible method for approximating influence via Geometric Ensemble
A Unified Diversity Measure for Multiagent Reinforcement Learning
RoboMamba: Efficient Vision-Language-Action Model for Robotic Reasoning and Manipulation
Federated Accelerated Stochastic Gradient Descent
RGMIL: Guide Your Multiple-Instance Learning Model with Regressor
Masked Autoencoders that Listen
Dialog-to-Action: Conversational Question Answering Over a Large-Scale Knowledge Base
Empirical Likelihood for Contextual Bandits
CWCL: Cross-Modal Transfer with Continuously Weighted Contrastive Loss
Optimistic Active Exploration of Dynamical Systems
Nonconvex Low-Rank Tensor Completion from Noisy Data
Coupled Generative Adversarial Networks
Parametric Local Metric Learning for Nearest Neighbor Classification
On the Model Shrinkage Effect of Gamma Process Edge Partition Models
Improving CLIP Training with Language Rewrites
BILCO: An Efficient Algorithm for Joint Alignment of Time Series
Softening Discrete Relaxation
Emergence of Hierarchical Layers in a Single Sheet of Self-Organizing Spiking Neurons
A Critical Look at the Consistency of Causal Estimation with Deep Latent Variable Models
Collaborative Filtering in a Non-Uniform World: Learning with the Weighted Trace Norm
Towards Effective Planning Strategies for Dynamic Opinion Networks
Residual Flows for Invertible Generative Modeling
Learning to Navigate in Cities Without a Map
From Canonical Correlation Analysis to Self-supervised Graph Neural Networks
Implicit Mixtures of Restricted Boltzmann Machines
Hamiltonian Latent Operators for content and motion disentanglement in image sequences
Adaptive Skip Intervals: Temporal Abstraction for Recurrent Dynamical Models
Understanding Model Selection for Learning in Strategic Environments
Progressive Feature Interaction Search for Deep Sparse Network
High-Order Attention Models for Visual Question Answering
3D-LLM: Injecting the 3D World into Large Language Models
Incorporating Context into Language Encoding Models for fMRI
Class-Distribution-Aware Pseudo-Labeling for Semi-Supervised Multi-Label Learning
Personalized Steering of Large Language Models: Versatile Steering Vectors Through Bi-directional Preference Optimization
The Privacy Onion Effect: Memorization is Relative
Exploring Consistency in Graph Representations: from Graph Kernels to Graph Neural Networks
TarGF: Learning Target Gradient Field to Rearrange Objects without Explicit Goal Specification
Dynamic Service Fee Pricing under Strategic Behavior: Actions as Instruments and Phase Transition
Dynamical segmentation of single trials from population neural data
Benchmarking Heterogeneous Treatment Effect Models through the Lens of Interpretability
Very Fast EM-Based Mixture Model Clustering Using Multiresolution Kd-Trees
StratLearner: Learning a Strategy for Misinformation Prevention in Social Networks
Taylor TD-learning
Clustering by Nonnegative Matrix Factorization Using Graph Random Walk
Efficient Stochastic Gradient Hard Thresholding
Generative Neurosymbolic Machines
Contrastive Graph Poisson Networks: Semi-Supervised Learning with Extremely Limited Labels
List-decodable Linear Regression
ShiftAddLLM: Accelerating Pretrained LLMs via Post-Training Multiplication-Less Reparameterization
Test-time Adaptation of Discriminative Models via Diffusion Generative Feedback
Improved Regret Bounds for Oracle-Based Adversarial Contextual Bandits
Weak-eval-Strong: Evaluating and Eliciting Lateral Thinking of LLMs with Situation Puzzles
Riemannian Continuous Normalizing Flows
Effective Dimension in Bandit Problems under Censorship
SG×P : A Sorghum Genotype × Phenotype Prediction Dataset and Benchmark
Adaptive Sparseness Using Jeffreys Prior
AP-10K: A Benchmark for Animal Pose Estimation in the Wild
Stochastic Multi-Armed-Bandit Problem with Non-stationary Rewards
Z-Forcing: Training Stochastic Recurrent Networks
Zero Time Waste: Recycling Predictions in Early Exit Neural Networks
Perspectives on Sparse Bayesian Learning
Learning a 1-layer conditional generative model in total variation
Deep RGB-D Canonical Correlation Analysis For Sparse Depth Completion
Text-space Graph Foundation Models: Comprehensive Benchmarks and New Insights
Capturing Failures of Large Language Models via Human Cognitive Biases
Periodic Activation Functions Induce Stationarity
Geometry Cloak: Preventing TGS-based 3D Reconstruction from Copyrighted Images
Last-Iterate Convergence for Generalized Frank-Wolfe in Monotone Variational Inequalities
Self-organization in Real Neurons: Anti-Hebb in 'Channel Space'?
Dynamic Tuning Towards Parameter and Inference Efficiency for ViT Adaptation
Generalization in Clustering with Unobserved Features
Breaking the Sample Size Barrier in Model-Based Reinforcement Learning with a Generative Model
AdaptSSR: Pre-training User Model with Augmentation-Adaptive Self-Supervised Ranking
Are These the Same Apple? Comparing Images Based on Object Intrinsics
Learning the 2-D Topology of Images
Test-Time Amendment with a Coarse Classifier for Fine-Grained Classification
Imitation with Neural Density Models
MAS: a multiplicative approximation scheme for probabilistic inference
Universal Growth in Production Economies
PUG: Photorealistic and Semantically Controllable Synthetic Data for Representation Learning
Asymptotics of representation learning in finite Bayesian neural networks
GenRL: Multimodal-foundation world models for generalization in embodied agents
Discrete-Convex-Analysis-Based Framework for Warm-Starting Algorithms with Predictions
Rand-NSG: Fast Accurate Billion-point Nearest Neighbor Search on a Single Node
FABind: Fast and Accurate Protein-Ligand Binding
Self-Supervised Learning with an Information Maximization Criterion
HUMANISE: Language-conditioned Human Motion Generation in 3D Scenes
Learning Object Bounding Boxes for 3D Instance Segmentation on Point Clouds
Learning Neural Set Functions Under the Optimal Subset Oracle
Team-Fictitious Play for Reaching Team-Nash Equilibrium in Multi-team Games
Parallel Streaming Wasserstein Barycenters
Revisiting Decomposable Submodular Function Minimization with Incidence Relations
Learnability of Influence in Networks
Comparison of Human and Machine Word Recognition
GenSDF: Two-Stage Learning of Generalizable Signed Distance Functions
Temporal Latent Bottleneck: Synthesis of Fast and Slow Processing Mechanisms in Sequence Learning
From PAC-Bayes Bounds to KL Regularization
Model Class Reliance for Random Forests
Automatic differentiation of nonsmooth iterative algorithms
Implicit Distributional Reinforcement Learning
Accelerated Adaptive Markov Chain for Partition Function Computation
UDPM: Upsampling Diffusion Probabilistic Models
A Game Theoretic Analysis of Additive Adversarial Attacks and Defenses
Managing Power Consumption and Performance of Computing Systems Using Reinforcement Learning
Neural Message Passing for Multi-Relational Ordered and Recursive Hypergraphs
Multiclass Performance Metric Elicitation
DropEdge not Foolproof: Effective Augmentation Method for Signed Graph Neural Networks
Estimating LASSO Risk and Noise Level
Module-Aware Optimization for Auxiliary Learning
Learning World Models for Unconstrained Goal Navigation
Inference with Minimal Communication: a Decision-Theoretic Variational Approach
Unleashing Multispectral Video's Potential in Semantic Segmentation: A Semi-supervised Viewpoint and New UAV-View Benchmark
Can you trust your model's uncertainty? Evaluating predictive uncertainty under dataset shift
Visual Programming for Step-by-Step Text-to-Image Generation and Evaluation
Causal Discovery from Subsampled Time Series with Proxy Variables
Escaping Saddle-Point Faster under Interpolation-like Conditions
Towards Data-Algorithm Dependent Generalization: a Case Study on Overparameterized Linear Regression
Complex-Cell Responses Derived from Center-Surround Inputs: The Surprising Power of Intradendritic Computation
Biologically-Plausible Determinant Maximization Neural Networks for Blind Separation of Correlated Sources
Optimal Sampling of Natural Images
Functionally Regionalized Knowledge Transfer for Low-resource Drug Discovery
Markov Random Fields for Collaborative Filtering
Understanding the Gains from Repeated Self-Distillation
Newton-Stein Method: A Second Order Method for GLMs via Stein's Lemma
Multi-armed Bandit Requiring Monotone Arm Sequences
Identifiability and generalizability from multiple experts in Inverse Reinforcement Learning
OBJECT 3DIT: Language-guided 3D-aware Image Editing
Performative Power
Neural Execution Engines: Learning to Execute Subroutines
Reflexive Associative Memories
Cooperative Multi-player Bandit Optimization
Expectation Consistent Free Energies for Approximate Inference
Non-Stationary Spectral Kernels
The Best of Both Worlds: On the Dilemma of Out-of-distribution Detection
The Observer-Observation Dilemma in Neuro-Forecasting
On the Optimal Weighted $\ell_2$ Regularization in Overparameterized Linear Regression
Thin and deep Gaussian processes
Emergent Communication for Rules Reasoning
Fully Bayesian inference for neural models with negative-binomial spiking
Hierarchical Gaussian Mixture based Task Generative Model for Robust Meta-Learning
Offline Contextual Bandits with High Probability Fairness Guarantees
Deep Correlated Prompting for Visual Recognition with Missing Modalities
Estimating Ego-Body Pose from Doubly Sparse Egocentric Video Data
Advancing Spiking Neural Networks for Sequential Modeling with Central Pattern Generators
An Algorithmic Framework For Differentially Private Data Analysis on Trusted Processors
Demystifying Orthogonal Monte Carlo and Beyond
Don't be so Monotone: Relaxing Stochastic Line Search in Over-Parameterized Models
Nearly Isometric Embedding by Relaxation
Faster Deep Reinforcement Learning with Slower Online Network
Online POMDP Planning with Anytime Deterministic Guarantees
A Kullback-Leibler Divergence Based Kernel for SVM Classification in Multimedia Applications
Multi-Agent Reinforcement Learning in Stochastic Networked Systems
Dissecting the Winning Solution of the HiggsML Challenge
ASL Citizen: A Community-Sourced Dataset for Advancing Isolated Sign Language Recognition
The Well: a Large-Scale Collection of Diverse Physics Simulations for Machine Learning
Linear Hinge Loss and Average Margin
Differentiable Clustering with Perturbed Spanning Forests
Overparameterization from Computational Constraints
A Simple and Optimal Policy Design for Online Learning with Safety against Heavy-tailed Risk
Ambiguous Images With Human Judgments for Robust Visual Event Classification
Outlier-Robust High-Dimensional Sparse Estimation via Iterative Filtering
Are Multiple Instance Learning Algorithms Learnable for Instances?
A new inference approach for training shallow and deep generalized linear models of noisy interacting neurons
Aligning Large Language Models with Representation Editing: A Control Perspective
Multiview Human Body Reconstruction from Uncalibrated Cameras
Geometric All-way Boolean Tensor Decomposition
SketchBoost: Fast Gradient Boosted Decision Tree for Multioutput Problems
3DOS: Towards 3D Open Set Learning - Benchmarking and Understanding Semantic Novelty Detection on Point Clouds
Estimating Causal Effects Identifiable from a Combination of Observations and Experiments
User-Level Differentially Private Learning via Correlated Sampling
Interior Point Implementations of Alternating Minimization Training
Local Phase Coherence and the Perception of Blur
DeNetDM: Debiasing by Network Depth Modulation
LocCa: Visual Pretraining with Location-aware Captioners
Hierarchical Multi-Agent Skill Discovery
Mathematical Capabilities of ChatGPT
Functional network reorganization in motor cortex can be explained by reward-modulated Hebbian learning
Efficient Generation of Structured Objects with Constrained Adversarial Networks
Iterative Deep Graph Learning for Graph Neural Networks: Better and Robust Node Embeddings
Angular Quantization-based Binary Codes for Fast Similarity Search
Smoothed Online Convex Optimization Based on Discounted-Normal-Predictor
Semi-Definite Programming by Perceptron Learning
On the Role of Noise in the Sample Complexity of Learning Recurrent Neural Networks: Exponential Gaps for Long Sequences
Surrogate Regret Bounds for Polyhedral Losses
Graduated Assignment for Joint Multi-Graph Matching and Clustering with Application to Unsupervised Graph Matching Network Learning
Algorithms for Non-negative Matrix Factorization
Robust Disentanglement of a Few Factors at a Time
Learning Discrete Concepts in Latent Hierarchical Models
Visual Reference Resolution using Attention Memory for Visual Dialog
Optimal Statistical Rates for Decentralised Non-Parametric Regression with Linear Speed-Up
Unbalanced Sobolev Descent
A Hodgkin-Huxley Type Neuron Model That Learns Slow Non-Spike Oscillations
Unifying Activation- and Timing-based Learning Rules for Spiking Neural Networks
Extracting Certainty from Uncertainty: Transductive Pairwise Classification from Pairwise Similarities
Graph Laplacian Regularization for Large-Scale Semidefinite Programming
Joint Optimization of Tree-based Index and Deep Model for Recommender Systems
Multiple Futures Prediction
Analysis and Design of Thompson Sampling for Stochastic Partial Monitoring
Improving the Privacy and Practicality of Objective Perturbation for Differentially Private Linear Learners
Efficient Temporal Action Segmentation via Boundary-aware Query Voting
Theoretical Insights Into Multiclass Classification: A High-dimensional Asymptotic View
Fast Efficient Hyperparameter Tuning for Policy Gradient Methods
Learning from Multiple Partially Observed Views - an Application to Multilingual Text Categorization
Audio Vision: Using Audio-Visual Synchrony to Locate Sounds
Stability and Observability
Kraken: Inherently Parallel Transformers For Efficient Multi-Device Inference
An Off-policy Policy Gradient Theorem Using Emphatic Weightings
AutoGO: Automated Computation Graph Optimization for Neural Network Evolution
Diffusion Hyperfeatures: Searching Through Time and Space for Semantic Correspondence
Predicting Short-Term Cognitive Change from Longitudinal Neuroimaging Analysis
Reverse engineering recurrent networks for sentiment classification reveals line attractor dynamics
Stochastic Ratio Matching of RBMs for Sparse High-Dimensional Inputs
Probabilistic Exponential Integrators
Communication-Efficient Topologies for Decentralized Learning with $O(1)$ Consensus Rate
Delayed Gradient Averaging: Tolerate the Communication Latency for Federated Learning
Meta-Album: Multi-domain Meta-Dataset for Few-Shot Image Classification
Short-Dot: Computing Large Linear Transforms Distributedly Using Coded Short Dot Products
Launch and Iterate: Reducing Prediction Churn
Quantized Random Projections and Non-Linear Estimation of Cosine Similarity
Provable Gaussian Embedding with One Observation
How to Fine-tune the Model: Unified Model Shift and Model Bias Policy Optimization
TA-MoE: Topology-Aware Large Scale Mixture-of-Expert Training
Episodic Multi-Task Learning with Heterogeneous Neural Processes
An Online Riemannian PCA for Stochastic Canonical Correlation Analysis
Graphical Models via Generalized Linear Models
Painless Stochastic Gradient: Interpolation, Line-Search, and Convergence Rates
Switch Packet Arbitration via Queue-Learning
Leveraging the Hints: Adaptive Bidding in Repeated First-Price Auctions
Chat-Scene: Bridging 3D Scene and Large Language Models with Object Identifiers
TOPA: Extending Large Language Models for Video Understanding via Text-Only Pre-Alignment
Patch n' Pack: NaViT, a Vision Transformer for any Aspect Ratio and Resolution
Loss Decoupling for Task-Agnostic Continual Learning
Fast Bayesian Coresets via Subsampling and Quasi-Newton Refinement
Fixed-Rank Approximation of a Positive-Semidefinite Matrix from Streaming Data
Locality and low-dimensions in the prediction of natural experience from fMRI
Policy Evaluation with Latent Confounders via Optimal Balance
Wasserstein $K$-means for clustering probability distributions
RORL: Robust Offline Reinforcement Learning via Conservative Smoothing
Efficient Minimax Signal Detection on Graphs
Efficiency for Free: Ideal Data Are Transportable Representations
Visual Decoding and Reconstruction via EEG Embeddings with Guided Diffusion
ResT V2: Simpler, Faster and Stronger
Clipped Stochastic Methods for Variational Inequalities with Heavy-Tailed Noise
GarmentLab: A Unified Simulation and Benchmark for Garment Manipulation
Robust and Faster Zeroth-Order Minimax Optimization: Complexity and Applications
Graph Neural Networks are Dynamic Programmers
VASA-1: Lifelike Audio-Driven Talking Faces Generated in Real Time
Learning Enhanced Representation for Tabular Data via Neighborhood Propagation
Relative Density-Ratio Estimation for Robust Distribution Comparison
Multi-Criteria Dimensionality Reduction with Applications to Fairness
Cryptographic Hardness of Score Estimation
An engine not a camera: Measuring performative power of online search
The Flip Side of the Reweighted Coin: Duality of Adaptive Dropout and Regularization
Estimating High-dimensional Non-Gaussian Multiple Index Models via Stein's Lemma
The Adversarial Consistency of Surrogate Risks for Binary Classification
Online and Differentially-Private Tensor Decomposition
ImOV3D: Learning Open Vocabulary Point Clouds 3D Object Detection from Only 2D Images
A Realizable Learning Task which Exhibits Overfitting
A Simple Decentralized Cross-Entropy Method
Unlock the Intermittent Control Ability of Model Free Reinforcement Learning
Discriminative Learning of Sum-Product Networks
On Fast Leverage Score Sampling and Optimal Learning
Efficient Learning using Forward-Backward Splitting
Learning Kernels with Random Features
Near Optimal Policy Optimization via REPS
On Iterative Krylov-Dogleg Trust-Region Steps for Solving Neural Networks Nonlinear Least Squares Problems
MultiScan: Scalable RGBD scanning for 3D environments with articulated objects
Distributed Machine Learning with Sparse Heterogeneous Data
Surface Learning with Applications to Lipreading
Posterior Contraction Rates for Matérn Gaussian Processes on Riemannian Manifolds
Understanding and Exploring the Network with Stochastic Architectures
Thy Friend is My Friend: Iterative Collaborative Filtering for Sparse Matrix Estimation
Policy Search via Density Estimation
Natural Sound Statistics and Divisive Normalization in the Auditory System
STEM: A Stochastic Two-Sided Momentum Algorithm Achieving Near-Optimal Sample and Communication Complexities for Federated Learning
AnimeRun: 2D Animation Visual Correspondence from Open Source 3D Movies
Stochastic Second-Order Methods Improve Best-Known Sample Complexity of SGD for Gradient-Dominated Functions
Communication/Computation Tradeoffs in Consensus-Based Distributed Optimization
Optimal Best-arm Identification in Linear Bandits
In the Eye of the Beholder: Robust Prediction with Causal User Modeling
Learning on Arbitrary Graph Topologies via Predictive Coding
MIDGArD: Modular Interpretable Diffusion over Graphs for Articulated Designs
Enhancing Robustness in Deep Reinforcement Learning: A Lyapunov Exponent Approach
Multi-Label Learning with Pairwise Relevance Ordering
Robust Value Function Approximation Using Bilinear Programming
ReFactor GNNs: Revisiting Factorisation-based Models from a Message-Passing Perspective
CARLANE: A Lane Detection Benchmark for Unsupervised Domain Adaptation from Simulation to multiple Real-World Domains
On the Epistemic Limits of Personalized Prediction
Hyperbolic Self-Organizing Maps for Semantic Navigation
Learning Distinct and Representative Modes for Image Captioning
Deep Predictive Coding Network with Local Recurrent Processing for Object Recognition
Random Sampling of States in Dynamic Programming
Differentially Private Decoupled Graph Convolutions for Multigranular Topology Protection
Advection Augmented Convolutional Neural Networks
Instance-wise Feature Grouping
Real Time Image Saliency for Black Box Classifiers
Augmentative Message Passing for Traveling Salesman Problem and Graph Partitioning
GoMatching: A Simple Baseline for Video Text Spotting via Long and Short Term Matching
Minimax Regret of Switching-Constrained Online Convex Optimization: No Phase Transition
OTKGE: Multi-modal Knowledge Graph Embeddings via Optimal Transport
Mean Field Residual Networks: On the Edge of Chaos
Physically Compatible 3D Object Modeling from a Single Image
Inference of Neural Dynamics Using Switching Recurrent Neural Networks
Understanding Double Descent Requires A Fine-Grained Bias-Variance Decomposition
Stochastic Gradient Descent-Ascent and Consensus Optimization for Smooth Games: Convergence Analysis under Expected Co-coercivity
Translating Locative Prepositions
Frustratingly Easy Test-Time Adaptation of Vision-Language Models
Value Prediction Network
UDON: Universal Dynamic Online distillatioN for generic image representations
Thin Junction Trees
Rethinking Gauss-Newton for learning over-parameterized models
WATT: Weight Average Test Time Adaptation of CLIP
A Loss Function for Generative Neural Networks Based on Watson's Perceptual Model
Emergent Correspondence from Image Diffusion
Knowledge Distillation from A Stronger Teacher
Towards Optimal Off-Policy Evaluation for Reinforcement Learning with Marginalized Importance Sampling
Model Adaptation: Historical Contrastive Learning for Unsupervised Domain Adaptation without Source Data
The Self-Normalized Estimator for Counterfactual Learning
In-Context Learning State Vector with Inner and Momentum Optimization
An Integrated Architecture of Adaptive Neural Network Control for Dynamic Systems
Deep Learning in Medical Image Registration: Magic or Mirage?
Exact Solutions to Time-Dependent MDPs