yusuke1997/dblp-id-title huggingface dataset:
Incrementally Learning Time-Varying Half Planes
iSCAN: Identifying Causal Mechanism Shifts among Nonlinear Additive Noise Models
Ask4Help: Learning to Leverage an Expert for Embodied Tasks
Removing the Feature Correlation Effect of Multiplicative Noise
Learning via Gaussian Herding
The Distortion of Binomial Voting Defies Expectation
Communication trade-offs for Local-SGD with large step size
Latent Diffusion for Language Generation
DC-Gaussian: Improving 3D Gaussian Splatting for Reflective Dash Cam Videos
Private estimation algorithms for stochastic block models and mixture models
Learnability Matters: Active Learning for Video Captioning
LLM Dataset Inference: Did you train on my dataset?
Cross-modal Prompts: Adapting Large Pre-trained Models for Audio-Visual Downstream Tasks
Generation of Internal Representation by alpha
Advances in Neural Information Processing Systems 3, [NIPS Conference, Denver, Colorado, USA, November 26-29, 1990]
Speaker-Follower Models for Vision-and-Language Navigation
HotBEV: Hardware-oriented Transformer-based Multi-View 3D Detector for BEV Perception
An Efficient Pessimistic-Optimistic Algorithm for Stochastic Linear Bandits with General Constraints
Semi-parametric Exponential Family PCA
Fair Online Bilateral Trade
Policy Continuation with Hindsight Inverse Dynamics
Identity Decoupling for Multi-Subject Personalization of Text-to-Image Models
Stability of $K$-Means Clustering
Enhancing Semi-Supervised Learning via Representative and Diverse Sample Selection
LACIE: Listener-Aware Finetuning for Calibration in Large Language Models
Generative Well-intentioned Networks
Detection and Localization of Changes in Conditional Distributions
Parallel Direction Method of Multipliers
A Bayesian Take on Gaussian Process Networks
Multi-class SVMs: From Tighter Data-Dependent Generalization Bounds to Novel Algorithms
Faster Differentially Private Convex Optimization via Second-Order Methods
Counterfactual Prediction for Bundle Treatment
Loss Dynamics of Temporal Difference Reinforcement Learning
Understanding and Improving Adversarial Collaborative Filtering for Robust Recommendation
Transfer Anomaly Detection by Inferring Latent Domain Representations
Embedding Dimension of Contrastive Learning and k-Nearest Neighbors
Approximate inference of marginals using the IBIA framework
Triangle Generative Adversarial Networks
Latent Weights Do Not Exist: Rethinking Binarized Neural Network Optimization
Deep Networks with Internal Selective Attention through Feedback Connections
PSDBoost: Matrix-Generation Linear Programming for Positive Semidefinite Matrices Learning
The Power of Extrapolation in Federated Learning
A General Greedy Approximation Algorithm with Applications
Results and Insights from Diagnostic Questions: The NeurIPS 2020 Education Challenge
Self-Similarity Priors: Neural Collages as Differentiable Fractal Representations
Explaining Datasets in Words: Statistical Models with Natural Language Parameters
Active Observing in Continuous-time Control
Sparse Kernel Principal Component Analysis
On Frank-Wolfe and Equilibrium Computation
Strategic Impatience in Go/NoGo versus Forced-Choice Decision-Making
SAMRS: Scaling-up Remote Sensing Segmentation Dataset with Segment Anything Model
Segment Anything in High Quality
Don't Stop Pretraining? Make Prompt-based Fine-tuning Powerful Learner
Factorizing Multivariate Function Classes
Minimax Dynamics of Optimally Balanced Spiking Networks of Excitatory and Inhibitory Neurons
Error Analysis of Tensor-Train Cross Approximation
EGODE: An Event-attended Graph ODE Framework for Modeling Rigid Dynamics
Optimal Scaling for Locally Balanced Proposals in Discrete Spaces
A Cross-Moment Approach for Causal Effect Estimation
A Novel Reinforcement Model of Birdsong Vocalization Learning
Learning Kernel Tests Without Data Splitting
Multi-modular Associative Memory
SparseLLM: Towards Global Pruning of Pre-trained Language Models
MEWS: Real-time Social Media Manipulation Detection and Analysis
Trained Rank Pruning for Efficient Deep Neural Networks
Offline Contextual Bayesian Optimization
Comparing Apples to Oranges: Learning Similarity Functions for Data Produced by Different Distributions
Learning Convolutional Feature Hierarchies for Visual Recognition
Reasoning Multi-Agent Behavioral Topology for Interactive Autonomous Driving
DeepMath - Deep Sequence Models for Premise Selection
Conformal Prediction using Conditional Histograms
Scalable Sensitivity and Uncertainty Analyses for Causal-Effect Estimates of Continuous-Valued Interventions
Insights From the NeurIPS 2021 NetHack Challenge
Fast Rank-1 Lattice Targeted Sampling for Black-box Optimization
IODA: Instance-Guided One-shot Domain Adaptation for Super-Resolution
Approximate Expectation Maximization
Empirical Gateaux Derivatives for Causal Inference
Digital Realisation of Self-Organizing Maps
Probabilistic Inference and Differential Privacy
Structural inference affects depth perception in the context of potential occlusion
Spiking PointNet: Spiking Neural Networks for Point Clouds
Improving Neural Program Synthesis with Inferred Execution Traces
One Model to Edit Them All: Free-Form Text-Driven Image Manipulation with Semantic Modulations
Learning Local Error Bars for Nonlinear Regression
Robust Meta-learning for Mixed Linear Regression with Small Batches
Retrieval & Fine-Tuning for In-Context Tabular Models
Median Selection Subset Aggregation for Parallel Inference
Bi-directional Weakly Supervised Knowledge Distillation for Whole Slide Image Classification
Adversarial Training from Mean Field Perspective
FinBen: A Holistic Financial Benchmark for Large Language Models
A Huber Loss Minimization Approach to Mean Estimation under User-level Differential Privacy
A Convergent O(n) Temporal-difference Algorithm for Off-policy Learning with Linear Function Approximation
Chasing Ghosts: Instruction Following as Bayesian State Tracking
Multi-Task Zipping via Layer-wise Neuron Sharing
Group Knowledge Transfer: Federated Learning of Large CNNs at the Edge
Debiasing Distributed Second Order Optimization with Surrogate Sketching and Scaled Regularization
Learning the Similarity of Documents: An Information-Geometric Approach to Document Retrieval and Categorization
Interpretable agent communication from scratch (with a generic visual processor emerging on the side)
Gaussian Process Bandits for Top-k Recommendations
Beyond Primal-Dual Methods in Bandits with Stochastic and Adversarial Constraints
Synergy of Clustering Multiple Back Propagation Networks
Physically-Based Face Rendering for NIR-VIS Face Recognition
Improving Online Algorithms via ML Predictions
Learning to Approximate a Bregman Divergence
Hidden Technical Debt in Machine Learning Systems
MutaPLM: Protein Language Modeling for Mutation Explanation and Engineering
Perturbation Learning Based Anomaly Detection
Learning Perceptual Inference by Contrasting
VFIMamba: Video Frame Interpolation with State Space Models
Efficient Optimization for Discriminative Latent Class Models
Improving Computational Efficiency in Visual Reinforcement Learning via Stored Embeddings
Taming Local Effects in Graph-based Spatiotemporal Forecasting
Non-rigid point set registration: Coherent Point Drift
Adversarial Self-Supervised Contrastive Learning
Ada-MSHyper: Adaptive Multi-Scale Hypergraph Transformer for Time Series Forecasting
Contextual Stochastic Bilevel Optimization
Model Selection in Gaussian Graphical Models: High-Dimensional Consistency of l 1 -regularized MLE
Grammar Transfer in a Second Order Recurrent Neural Network
Graph-Based Semi-Supervised Learning with Non-ignorable Non-response
Multi-Plane Program Induction with 3D Box Priors
Confidence Regulation Neurons in Language Models
Maximum Covariance Unfolding : Manifold Learning for Bimodal Data
Ensemble Nystrom Method
Repulsive Mixtures
Queueing Matching Bandits with Preference Feedback
ReTR: Modeling Rendering Via Transformer for Generalizable Neural Surface Reconstruction
Benchmarking Complex Instruction-Following with Multiple Constraints Composition
Rad-NeRF: Ray-decoupled Training of Neural Radiance Field
Generalization Guarantee of SGD for Pairwise Learning
GlucoSynth: Generating Differentially-Private Synthetic Glucose Traces
Reference Trustable Decoding: A Training-Free Augmentation Paradigm for Large Language Models
Attribution-Based Confidence Metric For Deep Neural Networks
Geometry-aware Two-scale PIFu Representation for Human Reconstruction
Blind One-microphone Speech Separation: A Spectral Learning Approach
Straggler Mitigation in Distributed Optimization Through Data Encoding
Scene Representation Networks: Continuous 3D-Structure-Aware Neural Scene Representations
Optimising Synchronisation Times for Mobile Devices
Consistent Estimation of Identifiable Nonparametric Mixture Models from Grouped Observations
Diverse Weight Averaging for Out-of-Distribution Generalization
DeepMed: Semiparametric Causal Mediation Analysis with Debiased Deep Learning
On Sparse Modern Hopfield Model
Verified Safe Reinforcement Learning for Neural Network Dynamic Models
Continuous Object Representation Networks: Novel View Synthesis without Target View Supervision
3D Object Recognition with Deep Belief Nets
Noisy Generalized Binary Search
Improving Neural Ordinary Differential Equations with Nesterov's Accelerated Gradient Method
ReplaceAnything3D: Text-Guided Object Replacement in 3D Scenes with Compositional Scene Representations
Enhancing Robustness of Last Layer Two-Stage Fair Model Corrections
Probabilistic Rule Realization and Selection
Learning Compositional Rules via Neural Program Synthesis
Counting Function Theorem for Multi-Layer Networks
Understanding variable importances in forests of randomized trees
Machine Learning for Health Workshop, ML4H@NeurIPS 2019, Vancouver, BC, Canada, 13 December 2019
A Neural Network Based Head Tracking System
A Single-Loop Accelerated Extra-Gradient Difference Algorithm with Improved Complexity Bounds for Constrained Minimax Optimization
Learning Hyper-Features for Visual Identification
Towards Reliable Model Selection for Unsupervised Domain Adaptation: An Empirical Study and A Certified Baseline
VERIFIED: A Video Corpus Moment Retrieval Benchmark for Fine-Grained Video Understanding
The promises and pitfalls of Stochastic Gradient Langevin Dynamics
HEMM: Holistic Evaluation of Multimodal Foundation Models
DEPrune: Depth-wise Separable Convolution Pruning for Maximizing GPU Parallelism
Capturing Semantically Meaningful Word Dependencies with an Admixture of Poisson MRFs
General bounds on the quality of Bayesian coresets
The Semi-Random Satisfaction of Voting Axioms
Deep Generative Models with Learnable Knowledge Constraints
CosNet: A Generalized Spectral Kernel Network
Motif-oriented influence maximization for viral marketing in large-scale social networks
Don't just prune by magnitude! Your mask topology is a secret weapon
A Toolbox for Construction and Analysis of Speech Datasets
DeBaRA: Denoising-Based 3D Room Arrangement Generation
Information Theoretic Lower Bounds for Information Theoretic Upper Bounds
Modeling Heterogeneous Hierarchies with Relation-specific Hyperbolic Cones
Low Distortion Block-Resampling with Spatially Stochastic Networks
Proceedings of the NIPS 2016 Workshop on Imperfect Decision Makers: Admitting Real-World Rationality, Barcelona, Spain, December 9, 2016
Hidden State Guidance: Improving Image Captioning Using an Image Conditioned Autoencoder
Regularizing by the Variance of the Activations' Sample-Variances
Structured Prediction with Stronger Consistency Guarantees
Causal Discovery from Event Sequences by Local Cause-Effect Attribution
Natasha 2: Faster Non-Convex Optimization Than SGD
U-DiTs: Downsample Tokens in U-Shaped Diffusion Transformers
SampDetox: Black-box Backdoor Defense via Perturbation-based Sample Detoxification
Successor Uncertainties: Exploration and Uncertainty in Temporal Difference Learning
Recurrent Space-time Graph Neural Networks
FL-WBC: Enhancing Robustness against Model Poisoning Attacks in Federated Learning from a Client Perspective
Using Collective Intelligence to Route Internet Traffic
Robust Deep Reinforcement Learning through Adversarial Loss
Avoiding Discrimination through Causal Reasoning
Optimal Treatment Allocation for Efficient Policy Evaluation in Sequential Decision Making
Semisupervised Clustering, AND-Queries and Locally Encodable Source Coding
The Geometry of Neural Nets' Parameter Spaces Under Reparametrization
Learning to Solve Quadratic Unconstrained Binary Optimization in a Classification Way
MoCa: Measuring Human-Language Model Alignment on Causal and Moral Judgment Tasks
S-Prompts Learning with Pre-trained Transformers: An Occam's Razor for Domain Incremental Learning
Constraint-Conditioned Policy Optimization for Versatile Safe Reinforcement Learning
Tactile DreamFusion: Exploiting Tactile Sensing for 3D Generation
Exact Rate-Distortion in Autoencoders via Echo Noise
Adversarial Counterfactual Environment Model Learning
A learning framework for nearest neighbor search
Online Learning with Primary and Secondary Losses
Deep Visual Analogy-Making
How does Inverse RL Scale to Large State Spaces? A Provably Efficient Approach
On the Noise Robustness of In-Context Learning for Text Generation
The CONDENSATION Algorithm - Conditional Density Propagation and Applications to Visual Tracking
Direct Optimization of Margins Improves Generalization in Combined Classifiers
Spherical Random Features for Polynomial Kernels
Recurrent Complex-Weighted Autoencoders for Unsupervised Object Discovery
Submodular meets Structured: Finding Diverse Subsets in Exponentially-Large Structured Item Sets
Neural Gaffer: Relighting Any Object via Diffusion
Energy-Inspired Models: Learning with Sampler-Induced Distributions
Scalable Inference for Gaussian Process Models with Black-Box Likelihoods
Dimensionality Reduction of Massive Sparse Datasets Using Coresets
Dimensionality Dependent PAC-Bayes Margin Bound
No Regrets for Learning the Prior in Bandits
Stochastic Adaptive Activation Function
Slice Sampling Reparameterization Gradients
Accelerating Quadratic Optimization with Reinforcement Learning
A New Discriminative Kernel From Probabilistic Models
Optimal Batched Best Arm Identification
Parameterizing Context: Unleashing the Power of Parameter-Efficient Fine-Tuning and In-Context Tuning for Continual Table Semantic Parsing
Learning in Hilbert vs. Banach Spaces: A Measure Embedding Viewpoint
Removing Hidden Confounding in Recommendation: A Unified Multi-Task Learning Approach
Fast and Flexible Monotonic Functions with Ensembles of Lattices
DiSC: Differential Spectral Clustering of Features
Generalization error in high-dimensional perceptrons: Approaching Bayes error with convex optimization
Sparse and Low-Rank Tensor Decomposition
Nonparametric Regressive Point Processes Based on Conditional Gaussian Processes
A Global Depth-Range-Free Multi-View Stereo Transformer Network with Pose Embedding
A Kernel Perspective on Distillation-based Collaborative Learning
Effective Adaptation in Multi-Task Co-Training for Unified Autonomous Driving
Shadowheart SGD: Distributed Asynchronous SGD with Optimal Time Complexity Under Arbitrary Computation and Communication Heterogeneity
SLANG: Fast Structured Covariance Approximations for Bayesian Deep Learning with Natural Gradient
Free-Rider and Conflict Aware Collaboration Formation for Cross-Silo Federated Learning
'N-Body' Problems in Statistical Learning
Smoothness, Low Noise and Fast Rates
Scaling up Continuous-Time Markov Chains Helps Resolve Underspecification
Extremal Mechanisms for Local Differential Privacy
A Similarity-preserving Network Trained on Transformed Images Recapitulates Salient Features of the Fly Motion Detection Circuit
Nonlinear scaling of resource allocation in sensory bottlenecks
GPS-Net: Graph-based Photometric Stereo Network
Probabilistic Inference of Alternative Splicing Events in Microarray Data
A 2 CiD 2 : Accelerating Asynchronous Communication in Decentralized Deep Learning
Iterative Structural Inference of Directed Graphs
Group Sparse Additive Machine
Out-of-Distribution Detection via Conditional Kernel Independence Model
Extreme Components Analysis
Non-Convex Bilevel Games with Critical Point Selection Maps
Reducing Shape-Radiance Ambiguity in Radiance Fields with a Closed-Form Color Estimation Method
Q-ViT: Accurate and Fully Quantized Low-bit Vision Transformer
Keeping LLMs Aligned After Fine-tuning: The Crucial Role of Prompt Templates
Integrated Modeling and Control Based on Reinforcement Learning
Rethinking Learnable Tree Filter for Generic Feature Transform
Dirichlet belief networks for topic structure learning
Understanding the Effective Receptive Field in Deep Convolutional Neural Networks
Implicit Regularization in Matrix Sensing via Mirror Descent
A Closer Look at the Robustness of Contrastive Language-Image Pre-Training (CLIP)
Identifying Learning Rules From Neural Network Observables
A Heat Diffusion Perspective on Geodesic Preserving Dimensionality Reduction
Towards Text Generation with Adversarially Learned Neural Outlines
Deceive D: Adaptive Pseudo Augmentation for GAN Training with Limited Data
Linear Causal Bandits: Unknown Graph and Soft Interventions
Latent Maximum Margin Clustering
Learning Non-Convergent Non-Persistent Short-Run MCMC Toward Energy-Based Model
Hyperbolic Procrustes Analysis Using Riemannian Geometry
Stochastic Window Transformer for Image Restoration
Learning to Share in Networked Multi-Agent Reinforcement Learning
Leveraging Early-Stage Robustness in Diffusion Models for Efficient and High-Quality Image Synthesis
Leveraging Topics and Audio Features with Multimodal Attention for Audio Visual Scene-Aware Dialog
An Information Retrieval Approach to Building Datasets for Hate Speech Detection
Unsupervised Learning of Object Keypoints for Perception and Control
Smoothed Analysis of Discrete Tensor Decomposition and Assemblies of Neurons
Fast Exact Leverage Score Sampling from Khatri-Rao Products with Applications to Tensor Decomposition
Exemplar Guided Active Learning
A Polar coordinate system represents syntax in large language models
Deep Differentiable Logic Gate Networks
Global Convergence of Least Squares EM for Demixing Two Log-Concave Densities
Learning Dynamic Belief Graphs to Generalize on Text-Based Games
On Second Order Behaviour in Augmented Neural ODEs
Structural and functional learning for learning language use
Graph-Driven Feature Extraction From Microarray Data Using Diffusion Kernels and Kernel CCA
Powerpropagation: A sparsity inducing weight reparameterisation
Regret Bounds for Thompson Sampling in Episodic Restless Bandit Problems
Optimization Methods for Sparse Pseudo-Likelihood Graphical Model Selection
Regularized Boost for Semi-Supervised Learning
Phoneme Classification using Constrained Variational Gaussian Process Dynamical System
Activation Sharing with Asymmetric Paths Solves Weight Transport Problem without Bidirectional Connection
Inverse Reinforcement Learning from a Gradient-based Learner
Extending Phase Mechanism to Differential Motion Opponency for Motion Pop-out
On the Robustness of Spectral Algorithms for Semirandom Stochastic Block Models
On a Modification to the Mean Field EM Algorithm in Factorial Learning
Safe Policy Optimization with Local Generalized Linear Function Approximations
Online learning with dynamics: A minimax perspective
Interpolating Item and User Fairness in Multi-Sided Recommendations
Semi-supervised Semantic Segmentation with Prototype-based Consistency Regularization
Bayesian Risk-Averse Q-Learning with Streaming Observations
Decompose Novel into Known: Part Concept Learning For 3D Novel Class Discovery
Discovering Neural Wirings
Beyond Concept Bottleneck Models: How to Make Black Boxes Intervenable?
Measuring Per-Unit Interpretability at Scale Without Humans
DAMEX: Dataset-aware Mixture-of-Experts for visual understanding of mixture-of-datasets
Functional Ensemble Distillation
A Fast Convoluted Story: Scaling Probabilistic Inference for Integer Arithmetics
360-MLC: Multi-view Layout Consistency for Self-training and Hyper-parameter Tuning
Learning Robust Hierarchical Patterns of Human Brain across Many fMRI Studies
Plug-and-Play Stability for Intracortical Brain-Computer Interfaces: A One-Year Demonstration of Seamless Brain-to-Text Communication
Gaussian Membership Inference Privacy
Fair Allocation of Indivisible Chores: Beyond Additive Costs
Geometric Analysis of Constrained Curves
An Analysis of Elo Rating Systems via Markov Chains
Bayesian Joint Estimation of Multiple Graphical Models
Regularizing Hidden States Enables Learning Generalizable Reward Model for LLMs
Importance Weighting and Variational Inference
Statistical Query Lower Bounds for List-Decodable Linear Regression
Active Learning from Peers
Counterfactual Data Augmentation using Locally Factored Dynamics
Temporal Dynamics of Generalization in Neural Networks
Rapid Convergence of the Unadjusted Langevin Algorithm: Isoperimetry Suffices
Stochastic Gradient Descent in Correlated Settings: A Study on Gaussian Processes
Improving Policy Learning via Language Dynamics Distillation
A Linear Time Active Learning Algorithm for Link Classification
Small random initialization is akin to spectral learning: Optimization and generalization guarantees for overparameterized low-rank matrix reconstruction
Towards Sample-Optimal Compressive Phase Retrieval with Sparse and Generative Priors
Stochastic Proximal Gradient Descent with Acceleration Techniques
Truly Nonparametric Online Variational Inference for Hierarchical Dirichlet Processes
Towards Practical Control of Singular Values of Convolutional Layers
Adaptive First-Order Methods Revisited: Convex Minimization without Lipschitz Requirements
Understanding Regularized Spectral Clustering via Graph Conductance
CluB: Cluster Meets BEV for LiDAR-Based 3D Object Detection
The Value Equivalence Principle for Model-Based Reinforcement Learning
Structural and Behavioral Evolution of Recurrent Networks
FilterNet: Harnessing Frequency Filters for Time Series Forecasting
Regularity as Intrinsic Reward for Free Play
Minimum Stein Discrepancy Estimators
Localized Zeroth-Order Prompt Optimization
GAMA: Generative Adversarial Multi-Object Scene Attacks
Discriminative Robust Transformation Learning
Nonparametric Greedy Algorithms for the Sparse Learning Problem
Bayesian Optimization for Iterative Learning
Convolutional Neural Network Architectures for Matching Natural Language Sentences
A Tractable Inference Perspective of Offline RL
ST-Adapter: Parameter-Efficient Image-to-Video Transfer Learning
Extending position/phase-shift tuning to motion energy neurons improves velocity discrimination
Diffeomorphic interpolation for efficient persistence-based topological optimization
An improved estimator of Variance Explained in the presence of noise
One for All: Simultaneous Metric and Preference Learning over Multiple Users
Reinforcing LLM Agents via Policy Optimization with Action Decomposition
Ranking via Robust Binary Classification
Learning to Select Exogenous Events for Marked Temporal Point Process
Interpretable Concept-Based Memory Reasoning
Recognizing Handwritten Digits Using Mixtures of Linear Models
An Analog VLSI Neural Network for Phase-based Machine Vision
On Blackbox Backpropagation and Jacobian Sensing
Information-theoretic Limits of Online Classification with Noisy Labels
Scaling Laws and Local Minima in Hebbian ICA
Learning Continuous Distributions: Simulations With Field Theoretic Priors
Advice Refinement in Knowledge-Based SVMs
Learning Deep Input-Output Stable Dynamics
ELASTIC: Numerical Reasoning with Adaptive Symbolic Compiler
Censored Quantile Regression Neural Networks for Distribution-Free Survival Analysis
Reward Design via Online Gradient Ascent
Online Pricing with Strategic and Patient Buyers
Thinking Forward: Memory-Efficient Federated Finetuning of Language Models
Unified representation of tractography and diffusion-weighted MRI data using sparse multidimensional arrays
Contrasting with Symile: Simple Model-Agnostic Representation Learning for Unlimited Modalities
Meta-Complementing the Semantics of Short Texts in Neural Topic Models
SGD Learns the Conjugate Kernel Class of the Network
Semi-Proximal Mirror-Prox for Nonsmooth Composite Minimization