yusuke1997/dblp-id-title huggingface dataset:
Proceedings of the 2003 Workshop on Interpreters, Virtual Machines and Emulators, IVME 2003, San Diego, California, USA, June 12, 2003
Comparative performance analysis of mobile runtimes on Intel XScale® technology
Performance issues and resolutions for the .NET runtime virtual machine
The parallel graph reduction machine, Alice
Toward the design of a parallel graph reduction machine: The MaRS project
Performance measurement of a G-machine implementation
Specification of reduction strategies in term rewriting systems
Graph Reduction, Proceedings of a Workshop, Santa Fé, New Mexico, USA, September 29 - October 1, 1986
Parallel execution of an equational language
Concurrent term rewriting as a model of computation
A new array operation
On the correspondence of lambda style reduction and combinator style reduction
Controlling reduction partial order in functional parallel programs
A flexible architectural study methodology
A simple abstract machine to execute supercombinators
Target code generation from G-machine code
Overview of Rediflow II Development
Unification of quantified terms
I-structures: Data structures for parallel computing
Parallel Graph Reduction on a Supercomputer: A Status Report
Graph reduction in a parallel virtual memory environment
Implementing logical variables on a graph reduction architecture
Arrays, non-determinism, side-effects, and parallelism: A functional perspective
Functional logic languages, Part I
Parallel garbage collection for graph machines
Head order reduction: A graph reduction scheme for the operational lambda calculus
Alfalfa: Distributed graph reduction on a hypercube multiprocessor
Rényi Divergence Variational Inference
Adaptive Data Debiasing through Bounded Exploration
Low-Rank Matrix and Tensor Completion via Adaptive Sampling
LLaVA-Med: Training a Large Language-and-Vision Assistant for Biomedicine in One Day
On Learning Intrinsic Rewards for Policy Gradient Methods
Generative causal explanations of black-box classifiers
Precision-Recall Balanced Topic Modelling
DABS 2.0: Improved Datasets and Algorithms for Universal Self-Supervision
On the Dimensionality of Word Embedding
Task-aware world model learning with meta weighting via bi-level optimization
Efficient multiple hyperparameter learning for log-linear models
YouTubePD: A Multimodal Benchmark for Parkinson's Disease Analysis
Joint Training of a Convolutional Network and a Graphical Model for Human Pose Estimation
Spiral Waves in Integrate-and-Fire Neural Networks
Generalized Method-of-Moments for Rank Aggregation
Characterizing Graph Datasets for Node Classification: Homophily-Heterophily Dichotomy and Beyond
A VLSI Neural Network for Color Constancy
Methods for Estimating the Computational Power and Generalization Capability of Neural Microcircuits
Learning the Semantic Correlation: An Alternative Way to Gain from Unlabeled Text
Efficient Pure Exploration in Adaptive Round model
Uprooting and Rerooting Higher-Order Graphical Models
Explanation-based Data Augmentation for Image Classification
AllSim: Simulating and Benchmarking Resource Allocation Policies in Multi-User Systems
Optimal Ridge Detection using Coverage Risk
Function Space Bayesian Pseudocoreset for Bayesian Neural Networks
Guiding The Last Layer in Federated Learning with Pre-Trained Models
Data-Efficient Learning with Neural Programs
Towards Understanding Learning Representations: To What Extent Do Different Neural Networks Learn the Same Representation
Neural Hybrid Automata: Learning Dynamics With Multiple Modes and Stochastic Transitions
Universal Rate-Distortion-Perception Representations for Lossy Compression
GACL: Exemplar-Free Generalized Analytic Continual Learning
Dynamic Prompt Learning: Addressing Cross-Attention Leakage for Text-Based Image Editing
Safe Model-based Reinforcement Learning with Stability Guarantees
Unravelling the Performance of Physics-informed Graph Neural Networks for Dynamical Systems
Basis Construction from Power Series Expansions of Value Functions
Local Similarity-Aware Deep Feature Embedding
Optimal Transport-based Labor-free Text Prompt Modeling for Sketch Re-identification
Behavior From the Void: Unsupervised Active Pre-Training
Finite Versus Infinite Neural Networks: an Empirical Study
Structural Risk Minimization for Nonparametric Time Series Prediction
UnlearnCanvas: Stylized Image Dataset for Enhanced Machine Unlearning Evaluation in Diffusion Models
Pyramid Attention For Source Code Summarization
Directed Regression
Environmental statistics and the trade-off between model-based and TD learning in humans
Information-based Adaptive Stimulus Selection to Optimize Communication Efficiency in Brain-Computer Interfaces
Cluster-Learngene: Inheriting Adaptive Clusters for Vision Transformers
A Probabilistic Framework for Nonlinearities in Stochastic Neural Networks
A Unified Model and Dimension for Interactive Estimation
Fast Rates in Stochastic Online Convex Optimization by Exploiting the Curvature of Feasible Sets
Differentially Private Stochastic Gradient Descent with Fixed-Size Minibatches: Tighter RDP Guarantees with or without Replacement
Decision-Focused Learning without Decision-Making: Learning Locally Optimized Decision Losses
EGSDE: Unpaired Image-to-Image Translation via Energy-Guided Stochastic Differential Equations
Dynamical Synapses Give Rise to a Power-Law Distribution of Neuronal Avalanches
Softstar: Heuristic-Guided Probabilistic Inference
Personalized Dictionary Learning for Heterogeneous Datasets
Contrastive learning of global and local features for medical image segmentation with limited annotations
Combinations of Weak Classifiers
The High Line: Exact Risk and Learning Rate Curves of Stochastic Adaptive Learning Rate Algorithms
Support Vector Machines with a Reject Option
Conditional Random Fields via Univariate Exponential Families
Optimal Uniform OPE and Model-based Offline Reinforcement Learning in Time-Homogeneous, Reward-Free and Task-Agnostic Settings
Graph Agreement Models for Semi-Supervised Learning
Effective Learning Requires Neuronal Remodeling of Hebbian Synapses
GenArtist: Multimodal LLM as an Agent for Unified Image Generation and Editing
Adaptive Proximal Gradient Method for Convex Optimization
Benchmarking the Attribution Quality of Vision Models
Breaking the Bandwidth Barrier: Geometrical Adaptive Entropy Estimation
Lipschitz regularity of deep neural networks: analysis and efficient estimation
Abide by the law and follow the flow: conservation laws for gradient flows
When Do Neural Nets Outperform Boosted Trees on Tabular Data?
Cost efficient gradient boosting
A Fast Scale-Invariant Algorithm for Non-negative Least Squares with Non-negative Data
Directional Hearing by the Mauthner System
A Neuromorphic Monaural Sound Localizer
Learning Causal Graphs with Small Interventions
A Segment-Based Automatic Language Identification System
Computing Kantorovich-Wasserstein Distances on d-dimensional histograms using (d+1)-partite graphs
Why the Metric Backbone Preserves Community Structure
Outlier Suppression: Pushing the Limit of Low-bit Transformer Language Models
Elementary Symmetric Polynomials for Optimal Experimental Design
Scale Adaptive Blind Deblurring
Reconciling Real Scores with Binary Comparisons: A New Logistic Based Model for Ranking
Efficient Nonparametric Smoothness Estimation
Matrix Completion with Noisy Side Information
Enhancing LLM's Cognition via Structurization
Neural-Symbolic Entangled Framework for Complex Query Answering
Mitigating Reward Overoptimization via Lightweight Uncertainty Estimation
A Competitive Modular Connectionist Architecture
C2FAR: Coarse-to-Fine Autoregressive Networks for Precise Probabilistic Forecasting
Succinct and Robust Multi-Agent Communication With Temporal Message Control
A Little Robustness Goes a Long Way: Leveraging Robust Features for Targeted Transfer Attacks
Reliable Estimation of KL Divergence using a Discriminator in Reproducing Kernel Hilbert Space
Scalable Interpretability via Polynomials
Integrated accounts of behavioral and neuroimaging data using flexible recurrent neural network models
Nonparametric Latent Feature Models for Link Prediction
Provably Safe Reinforcement Learning with Step-wise Violation Constraints
Learning Semantic-aware Normalization for Generative Adversarial Networks
Learning unbelievable probabilities
Assessing SATNet's Ability to Solve the Symbol Grounding Problem
Generalization Error and Algorithmic Convergence of Median Boosting
Theory and Approximate Solvers for Branched Optimal Transport with Multiple Sources
The tree autoencoder model, with application to hierarchical data visualization
Controlling Text-to-Image Diffusion by Orthogonal Finetuning
GMMSeg: Gaussian Mixture based Generative Semantic Segmentation Models
Optimal Guarantees for Algorithmic Reproducibility and Gradient Complexity in Convex Optimization
Density of States Prediction of Crystalline Materials via Prompt-guided Multi-Modal Transformer
Limiting Extrapolation in Linear Approximate Value Iteration
A Flexible Framework for Designing Trainable Priors with Adaptive Smoothing and Game Encoding
Proceedings of the 1st Workshop on Feature Extraction: Modern Questions and Challenges, FE 2015, co-located with the 29th Annual Conference on Neural Information Processing Systems (NIPS 2015), Montreal, Canada, December 11-12, 2015
Beyond Disagreement-Based Agnostic Active Learning
A Unifying Perspective of Parametric Policy Search Methods for Markov Decision Processes
MultiMoDN - Multimodal, Multi-Task, Interpretable Modular Networks
HM-BiTAM: Bilingual Topic Exploration, Word Alignment, and Translation
A Taxonomy of Challenges to Curating Fair Datasets
Global Update Tracking: A Decentralized Learning Algorithm for Heterogeneous Data
Three-Way Trade-Off in Multi-Objective Learning: Optimization, Generalization and Conflict-Avoidance
A Probabilistic Model of Social Decision Making based on Reward Maximization
Temporal Coding using the Response Properties of Spiking Neurons
Factor Group-Sparse Regularization for Efficient Low-Rank Matrix Recovery
Hierarchical spike coding of sound
Unsupervised Learning of Disentangled and Interpretable Representations from Sequential Data
Yo'LLaVA: Your Personalized Language and Vision Assistant
To Stay or Not to Stay in the Pre-train Basin: Insights on Ensembling in Transfer Learning
Mix-of-Show: Decentralized Low-Rank Adaptation for Multi-Concept Customization of Diffusion Models
Characterizing Generalization under Out-Of-Distribution Shifts in Deep Metric Learning
RefDrop: Controllable Consistency in Image or Video Generation via Reference Feature Guidance
Neural Networks with Recurrent Generative Feedback
Learning Low-Dimensional Metrics
Collaborative Uncertainty in Multi-Agent Trajectory Forecasting
Solid Harmonic Wavelet Scattering: Predicting Quantum Molecular Energy from Invariant Descriptors of 3D Electronic Densities
Algorithms with Prediction Portfolios
OmniVL: One Foundation Model for Image-Language and Video-Language Tasks
Leveraging sparse and shared feature activations for disentangled representation learning
Encoding Robustness to Image Style via Adversarial Feature Perturbations
On the Efficient Minimization of Classification Calibrated Surrogates
Data Augmentation for Compositional Data: Advancing Predictive Models of the Microbiome
Distance Metric Learning for Large Margin Nearest Neighbor Classification
Classifying with Gaussian Mixtures and Clusters
Advances in Neural Information Processing Systems 8, NIPS, Denver, CO, USA, November 27-30, 1995
Learning Nonlinear Dynamical Systems Using an EM Algorithm
Spike-timing Dependent Plasticity and Mutual Information Maximization for a Spiking Neuron Model
Transfer Learning via ℓ 1 Regularization
Explicit Tradeoffs between Adversarial and Natural Distributional Robustness
Learning with Invariance via Linear Functionals on Reproducing Kernel Hilbert Space
Is Behavior Cloning All You Need? Understanding Horizon in Imitation Learning
Multi-Level Active Prediction of Useful Image Annotations for Recognition
Embedding Trajectory for Out-of-Distribution Detection in Mathematical Reasoning
Variance Reduction Techniques for Gradient Estimates in Reinforcement Learning
Gold-standard solutions to the Schrödinger equation using deep learning: How much physics do we need?
On Oracle-Efficient PAC RL with Rich Observations
Comparing Biases for Minimal Network Construction with Back-Propagation
Displacement-Invariant Matching Cost Learning for Accurate Optical Flow Estimation
Learning to Generate Realistic Noisy Images via Pixel-level Noise-aware Adversarial Training
Associating Objects and Their Effects in Video through Coordination Games
Real3D-AD: A Dataset of Point Cloud Anomaly Detection
Learning Physics Constrained Dynamics Using Autoencoders
Learning Cooperative Trajectory Representations for Motion Forecasting
Towards General Loop Invariant Generation: A Benchmark of Programs with Memory Manipulation
CaSPR: Learning Canonical Spatiotemporal Point Cloud Representations
Reflection, Refraction, and Hamiltonian Monte Carlo
What If the Input is Expanded in OOD Detection?
An Analog VLSI Model of the Fly Elementary Motion Detector
Safe Adaptive Importance Sampling
Friendly Noise against Adversarial Noise: A Powerful Defense against Data Poisoning Attack
GraphMETRO: Mitigating Complex Graph Distribution Shifts via Mixture of Aligned Experts
A Fast, Consistent Kernel Two-Sample Test
Invisible Image Watermarks Are Provably Removable Using Generative AI
On the Power of Neural Networks for Solving Hard Problems
SatBird: a Dataset for Bird Species Distribution Modeling using Remote Sensing and Citizen Science Data
Stylus: Automatic Adapter Selection for Diffusion Models
The Entropy Regularization Information Criterion
DenseFusion-1M: Merging Vision Experts for Comprehensive Multimodal Perception
When are Kalman-Filter Restless Bandits Indexable?
Active Structure Learning of Causal DAGs via Directed Clique Trees
You Don't Need Domain-Specific Data Augmentations When Scaling Self-Supervised Learning
Practical Near Neighbor Search via Group Testing
Fictitious Play for Mean Field Games: Continuous Time Analysis and Applications
Flattening a Hierarchical Clustering through Active Learning
Understanding the Role of Equivariance in Self-supervised Learning
Stopping Bayesian Optimization with Probabilistic Regret Bounds
Revisiting Adversarial Robustness Distillation from the Perspective of Robust Fairness
Algorithm-hardware Co-design for Deformable Convolution
Unsupervised Scalable Representation Learning for Multivariate Time Series
Algorithmic Capabilities of Random Transformers
Statistical Analysis of Semi-Supervised Regression
Fast Kernel Learning for Multidimensional Pattern Extrapolation
Asynchronous Perception Machine for Efficient Test Time Training
Learning to Drop Out: An Adversarial Approach to Training Sequence VAEs
The Scandinavian Embedding Benchmarks: Comprehensive Assessment of Multilingual and Monolingual Text Embedding
Carrot and Stick: Eliciting Comparison Data and Beyond
Necessary and Sufficient Conditions for Optimal Decision Trees using Dynamic Programming
PHYRE: A New Benchmark for Physical Reasoning
Boosting with Maximum Adaptive Sampling
Passport-aware Normalization for Deep Model Protection
Embroid: Unsupervised Prediction Smoothing Can Improve Few-Shot Classification
Iterative Connecting Probability Estimation for Networks
Manifold-tiling Localized Receptive Fields are Optimal in Similarity-preserving Neural Networks
A Hybrid Linear/Nonlinear Approach to Channel Equalization Problems
From Margin to Sparsity
Learning Large-Scale Poisson DAG Models based on OverDispersion Scoring
Adam on Local Time: Addressing Nonstationarity in RL with Relative Adam Timesteps
Active Bidirectional Coupling in a Cochlear Chip
OpenGSL: A Comprehensive Benchmark for Graph Structure Learning
Learning Curves for Stochastic Gradient Descent in Linear Feedforward Networks
PopSign ASL v1.0: An Isolated American Sign Language Dataset Collected via Smartphones
Stochastic blockmodel approximation of a graphon: Theory and consistent estimation
Continual Learning In Environments With Polynomial Mixing Times
Joint Prompt Optimization of Stacked LLMs using Variational Inference
Linear regression without correspondence
Point-M2AE: Multi-scale Masked Autoencoders for Hierarchical Point Cloud Pre-training
Exploit Reward Shifting in Value-Based Deep-RL: Optimistic Curiosity-Based Exploration and Conservative Exploitation via Linear Reward Shaping
ECG-QA: A Comprehensive Question Answering Dataset Combined With Electrocardiogram
Towards Dynamic Message Passing on Graphs
ControlSynth Neural ODEs: Modeling Dynamical Systems with Guaranteed Convergence
A unified theory for the origin of grid cells through the lens of pattern formation
Are Labels Required for Improving Adversarial Robustness?
PreferenceNet: Encoding Human Preferences in Auction Design with Deep Learning
Budgeted Optimization with Concurrent Stochastic-Duration Experiments
Robust Counterfactual Explanations on Graph Neural Networks
A New Convex Relaxation for Tensor Completion
Nonparametric Contextual Bandits in Metric Spaces with Unknown Metric
3D Photography Based Neural Network Craniosynostosis Triaging System
On the Convergence Theory for Hessian-Free Bilevel Algorithms
Discriminative Learning for Label Sequences via Boosting
Understanding and Improving Fast Adversarial Training
Binary Rating Estimation with Graph Side Information
Multi-Agent First Order Constrained Optimization in Policy Space
Efficient Pattern Recognition Using a New Transformation Distance
Learning to Adapt via Latent Domains for Adaptive Semantic Segmentation
Learning to Share and Hide Intentions using Information Regularization
Incrementality Bidding via Reinforcement Learning under Mixed and Delayed Rewards
Speech Denoising and Dereverberation Using Probabilistic Models
A Bayesian Framework for Tilt Perception and Confidence
Fixed-Support Wasserstein Barycenters: Computational Hardness and Fast Algorithm
Distilling Representations from GAN Generator via Squeeze and Span
CORL: Research-oriented Deep Offline Reinforcement Learning Library
NU-MCC: Multiview Compressive Coding with Neighborhood Decoder and Repulsive UDF
Mean-field theory of graph neural networks in graph partitioning
UAV3D: A Large-scale 3D Perception Benchmark for Unmanned Aerial Vehicles
Off to new Shores: A Dataset & Benchmark for (near-)coastal Flood Inundation Forecasting
Composite Multiclass Losses
A Win-win Deal: Towards Sparse and Robust Pre-trained Language Models
A Unified Framework for Data Poisoning Attack to Graph-based Semi-supervised Learning
A Topographic Support Vector Machine: Classification Using Local Label Configurations
SuperVLAD: Compact and Robust Image Descriptors for Visual Place Recognition
SLIP: Learning to predict in unknown dynamical systems with long-term memory
The Noisy-Logical Distribution and its Application to Causal Inference
Decentralized Accelerated Proximal Gradient Descent
Why do We Need Large Batchsizes in Contrastive Learning? A Gradient-Bias Perspective
An Information-Theoretic Evaluation of Generative Models in Learning Multi-modal Distributions
Learning from brains how to regularize machines
Maximizing Induced Cardinality Under a Determinantal Point Process
Evaluating Protein Transfer Learning with TAPE
Complex Inference in Neural Circuits with Probabilistic Population Codes and Topic Models
Language-Driven Interactive Traffic Trajectory Generation
Multi-Task Averaging
Low Rank Approximation Lower Bounds in Row-Update Streams
A Channel Coding Benchmark for Meta-Learning
LinGCN: Structural Linearized Graph Convolutional Network for Homomorphically Encrypted Inference
A novel variational form of the Schatten-$p$ quasi-norm
Adapting to the Shifting Intent of Search Queries
Model-Agnostic Private Learning
A General Large Neighborhood Search Framework for Solving Integer Linear Programs
Efficient Online Inference for Bayesian Nonparametric Relational Models
How To Make the Gradients Small Stochastically: Even Faster Convex and Nonconvex SGD
Hierarchical Penalization
Fine-Grained Dynamic Head for Object Detection
Agnostic PAC-Learning of Functions on Analog Neural Nets
Inhomogeneous Hypergraph Clustering with Applications
Soft-Unification in Deep Probabilistic Logic
Stochastic Distributed Optimization under Average Second-order Similarity: Algorithms and Analysis
Two-Stage Learning to Defer with Multiple Experts
Input-Aware Dynamic Backdoor Attack
Advances in Neural Information Processing Systems 23: 24th Annual Conference on Neural Information Processing Systems 2010. Proceedings of a meeting held 6-9 December 2010, Vancouver, British Columbia, Canada
AGEM: Solving Linear Inverse Problems via Deep Priors and Sampling
Transferring Expectations in Model-based Reinforcement Learning
Predicting Clinically Definite Multiple Sclerosis from Onset Using SVM
Continuous Sigmoidal Belief Networks Trained using Slice Sampling
Variance-based Regularization with Convex Objectives
VeXKD: The Versatile Integration of Cross-Modal Fusion and Knowledge Distillation for 3D Perception
Using Random Effects to Account for High-Cardinality Categorical Features and Repeated Measures in Deep Neural Networks
DiffuseBot: Breeding Soft Robots With Physics-Augmented Generative Diffusion Models
Federated Learning over Connected Modes
A Versatile Diffusion Transformer with Mixture of Noise Levels for Audiovisual Generation
Faster Randomized Infeasible Interior Point Methods for Tall/Wide Linear Programs
Reverse Multi-Label Learning
NeuralGF: Unsupervised Point Normal Estimation by Learning Neural Gradient Function
Whence Sparseness?
Hamiltonian Monte Carlo using an adjoint-differentiated Laplace approximation: Bayesian inference for latent Gaussian models and beyond
SPA: A Graph Spectral Alignment Perspective for Domain Adaptation
Smoothie: Label Free Language Model Routing
The Cocktail Party Problem: Speech/Data Signal Separation Comparison between Backpropagation and SONN
Learning from discriminative feature feedback
Riemannian Diffusion Models
Maximum Expected Hitting Cost of a Markov Decision Process and Informativeness of Rewards
From Weighted Classification to Policy Search
Semi-Supervised Learning with Decision Trees: Graph Laplacian Tree Alternating Optimization
NeurWIN: Neural Whittle Index Network For Restless Bandits Via Deep RL
Entropy Estimations Using Correlated Symmetric Stable Random Projections
Achieving O(ε -1.5 ) Complexity in Hessian/Jacobian-free Stochastic Bilevel Optimization
Efficient Training of Visual Transformers with Small Datasets
Structured Neural-PI Control with End-to-End Stability and Output Tracking Guarantees
Regret-Based Pruning in Extensive-Form Games
Context dependent amplification of both rate and event-correlation in a VLSI network of spiking neurons
Probabilistic detection of short events, with application to critical care monitoring
State Aggregation Learning from Markov Transition Data
Reconstruction of Manipulated Garment with Guided Deformation Prior
DreamSim: Learning New Dimensions of Human Visual Similarity using Synthetic Data
Non-parametric Approximate Dynamic Programming via the Kernel Method
HIQL: Offline Goal-Conditioned RL with Latent States as Actions
Modular Autoencoders for Ensemble Feature Extraction
PowerSGD: Practical Low-Rank Gradient Compression for Distributed Optimization
A Comparison of Image Processing Techniques for Visual Speech Recognition Applications
Decomposed Knowledge Distillation for Class-Incremental Semantic Segmentation
Using Trusted Data to Train Deep Networks on Labels Corrupted by Severe Noise
A Network of Localized Linear Discriminants
Kernel Dimensionality Reduction for Supervised Learning
Width-based Lookaheads with Learnt Base Policies and Heuristics Over the Atari-2600 Benchmark
Hard Prompts Made Easy: Gradient-Based Discrete Optimization for Prompt Tuning and Discovery
Optimal Kernel Shapes for Local Linear Regression
Normal-GS: 3D Gaussian Splatting with Normal-Involved Rendering
Kernel Design Using Boosting
Local Decorrelation For Improved Pedestrian Detection
Distributed Variational Inference in Sparse Gaussian Process Regression and Latent Variable Models
EGSST: Event-based Graph Spatiotemporal Sensitive Transformer for Object Detection