yusuke1997/dblp-id-title huggingface dataset:
Bias and Generalization in Deep Generative Models: An Empirical Study
Time-Independent Information-Theoretic Generalization Bounds for SGLD
Hessian Eigenspectra of More Realistic Nonlinear Models
Feature Transitions with Saccadic Search: Size, Color, and Orientation Are Not Alike
From News to Forecast: Integrating Event Analysis in LLM-Based Time Series Forecasting with Reflection
IKEA-Manual: Seeing Shape Assembly Step by Step
Information Design in Multi-Agent Reinforcement Learning
A general agnostic active learning algorithm
CSFCube - A Test Collection of Computer Science Research Articles for Faceted Query by Example
Meta-Controller: Few-Shot Imitation of Unseen Embodiments and Tasks in Continuous Control
Sample-Efficient Learning of Correlated Equilibria in Extensive-Form Games
Bootstrapped Transformer for Offline Reinforcement Learning
Nonlinear MCMC for Bayesian Machine Learning
Learning Stable Deep Dynamics Models
On the Overlooked Pitfalls of Weight Decay and How to Mitigate Them: A Gradient-Norm Perspective
ContactField: Implicit Field Representation for Multi-Person Interaction Geometry
Selective Sampling and Imitation Learning via Online Regression
Scalars are universal: Equivariant machine learning, structured like classical physics
Online Optimization with Memory and Competitive Control
Unifying Voxel-based Representation with Transformer for 3D Object Detection
Causal discovery in multiple models from different experiments
A Boolean Task Algebra for Reinforcement Learning
DIFFER: Decomposing Individual Reward for Fair Experience Replay in Multi-Agent Reinforcement Learning
A matching pursuit approach to sparse Gaussian process regression
Learning Confidence Sets using Support Vector Machines
Lips Are Lying: Spotting the Temporal Inconsistency between Audio and Visual in Lip-Syncing DeepFakes
Finding Discriminative Filters for Specific Degradations in Blind Super-Resolution
On fast approximate submodular minimization
Aggregating Optimistic Planning Trees for Solving Markov Decision Processes
General Stochastic Networks for Classification
No-regret Algorithms for Fair Resource Allocation
Consistency Regularization for Certified Robustness of Smoothed Classifiers
Instance-optimal Mean Estimation Under Differential Privacy
Transportability from Multiple Environments with Limited Experiments
The Fine-Grained Complexity of Gradient Computation for Training Large Language Models
Is Approval Voting Optimal Given Approval Votes?
Structured Energy Network As a Loss
Fairness Transferability Subject to Bounded Distribution Shift
MultiFusion: Fusing Pre-Trained Models for Multi-Lingual, Multi-Modal Image Generation
Phased Consistency Models
DeltaDock: A Unified Framework for Accurate, Efficient, and Physically Reliable Molecular Docking
Ethical Considerations for Responsible Data Curation
Learning with Temporal Derivatives in Pulse-Coded Neuronal Systems
Rethinking Deep Thinking: Stable Learning of Algorithms using Lipschitz Constraints
Selective Labeling via Error Bound Minimization
Identifying Spatio-Temporal Drivers of Extreme Events
Identifying good directions to escape the NTK regime and efficiently learn low-degree plus sparse polynomials
Does the Wake-sleep Algorithm Produce Good Density Estimators?
An Analysis of Tokenization: Transformers under Markov Data
Optimal Response Initiation: Why Recent Experience Matters
Reward Scale Robustness for Proximal Policy Optimization via DreamerV3 Tricks
Finite-Time Analysis for Double Q-learning
Fast Learning in Multi-Resolution Hierarchies
Sub-linear Regret Bounds for Bayesian Optimisation in Unknown Search Spaces
Learning Time-Invariant Representations for Individual Neurons from Population Dynamics
Private Stochastic Convex Optimization with Optimal Rates
Distributed Least Squares in Small Space via Sketching and Bias Reduction
MaCow: Masked Convolutional Generative Flow
GANs for All: Supporting Fun and Intuitive Exploration of GAN Latent Spaces
Online Classification on a Budget
Convex Elicitation of Continuous Properties
On the Local Minima of the Empirical Risk
PAC-Bayes under potentially heavy tails
Reducing Noise in GAN Training with Variance Reduced Extragradient
Conversational Crowdsourcing
Learning Certified Individually Fair Representations
Lessons learned from the NeurIPS 2021 MetaDL challenge: Backbone fine-tuning without episodic meta-learning dominates for few-shot learning image classification
Zeta Hull Pursuits: Learning Nonconvex Data Hulls
Predictive App roaches for Choosing Hyperparameters in Gaussian Processes
Chaining Mutual Information and Tightening Generalization Bounds
BRUNO: A Deep Recurrent Model for Exchangeable Data
GDeR: Safeguarding Efficiency, Balancing, and Robustness via Prototypical Graph Pruning
MMA Regularization: Decorrelating Weights of Neural Networks by Maximizing the Minimal Angles
From which world is your graph
Limits, approximation and size transferability for GNNs on sparse graphs via graphops
MicroNet for Efficient Language Modeling
Practical exact algorithm for trembling-hand equilibrium refinements in games
A sandbox for prediction and integration of DNA, RNA, and proteins in single cells
Iterative Scaled Trust-Region Learning in Krylov Subspaces via Pearlmutter's Implicit Sparse Hessian-Vector Multiply
Auxiliary Task Reweighting for Minimum-data Learning
A Domain Agnostic Measure for Monitoring and Evaluating GANs
Amortizing intractable inference in diffusion models for vision, language, and control
Union of Intersections (UoI) for Interpretable Data Driven Discovery and Prediction
A Connectionist Technique for Accelerated Textual Input: Letting a Network Do the Typing
Neural networks grown and self-organized by noise
Robust Subspace Approximation in a Stream
AndroidInTheWild: A Large-Scale Dataset For Android Device Control
Entropy and Inference, Revisited
Not All Diffusion Model Activations Have Been Evaluated as Discriminative Features
Canonical Time Warping for Alignment of Human Behavior
Alexa Arena: A User-Centric Interactive Platform for Embodied AI
Deep Neural Networks as Point Estimates for Deep Gaussian Processes
Barely Random Algorithms and Collective Metrical Task Systems
Distribution-Calibrated Hierarchical Classification
A Dimension-Independent Generalization Bound for Kernel Supervised Principal Component Analysis
Exactness of Approximate MAP Inference in Continuous MRFs
Conditional Random Field Autoencoders for Unsupervised Structured Prediction
Binet-Cauchy Kernels
Noise2Score: Tweedie's Approach to Self-Supervised Image Denoising without Clean Images
Differentiable Spline Approximations
Halting in Random Walk Kernels
Variational inference for Markov jump processes
On the Power of Differentiable Learning versus PAC and SQ Learning
Near-Isometric Properties of Kronecker-Structured Random Tensor Embeddings
An Efficient Pruning Algorithm for Robust Isotonic Regression
Pick-a-Pic: An Open Dataset of User Preferences for Text-to-Image Generation
Image Copy Detection for Diffusion Models
A Risk Minimization Principle for a Class of Parzen Estimators
Full-Gradient Representation for Neural Network Visualization
Efficient Beam Tree Recursion
DFRD: Data-Free Robustness Distillation for Heterogeneous Federated Learning
Safety Guarantees for Neural Network Dynamic Systems via Stochastic Barrier Functions
On Testing for Biases in Peer Review
Towards Stable Backdoor Purification through Feature Shift Tuning
INQUIRE: A Natural World Text-to-Image Retrieval Benchmark
Group-Fair Online Allocation in Continuous Time
Improved Silicon Cochlea using Compatible Lateral Bipolar Transistors
A Gamified Crowdsourcing Framework for Data-Driven Co-Creation of Policy Making and Social Foresight
Transferable Calibration with Lower Bias and Variance in Domain Adaptation
Optimistic Concurrency Control for Distributed Unsupervised Learning
Memory-Efficient LLM Training with Online Subspace Descent
Hyperbolic VAE via Latent Gaussian Distributions
ALICE: Towards Understanding Adversarial Learning for Joint Distribution Matching
ConMe: Rethinking Evaluation of Compositional Reasoning for Modern VLMs
Fixed Confidence Best Arm Identification in the Bayesian Setting
Predicting Parameters in Deep Learning
Exploitability Minimization in Games and Beyond
A flow-based latent state generative model of neural population responses to natural images
MultiPull: Detailing Signed Distance Functions by Pulling Multi-Level Queries at Multi-Step
BIG & QUIC: Sparse Inverse Covariance Estimation for a Million Variables
A Dual Framework for Low-rank Tensor Completion
Sample-Then-Optimize Batch Neural Thompson Sampling
State2Explanation: Concept-Based Explanations to Benefit Agent Learning and User Understanding
MOReL: Model-Based Offline Reinforcement Learning
A Layer-Wise Natural Gradient Optimizer for Training Deep Neural Networks
Validated Image Caption Rating Dataset
Evaluation beyond Task Performance: Analyzing Concepts in AlphaZero in Hex
ReLIZO: Sample Reusable Linear Interpolation-based Zeroth-order Optimization
See and Think: Disentangling Semantic Scene Completion
SpikedAttention: Training-Free and Fully Spike-Driven Transformer-to-SNN Conversion with Winner-Oriented Spike Shift for Softmax Operation
Intrinsic dimension of data representations in deep neural networks
Convolutional Neural Networks with Intra-Layer Recurrent Connections for Scene Labeling
Hierarchical Integration Diffusion Model for Realistic Image Deblurring
Efficient Phi-Regret Minimization in Extensive-Form Games via Online Mirror Descent
Size of Multilayer Networks for Exact Learning: Analytic Approach
Regret Matching+: (In)Stability and Fast Convergence in Games
FewViewGS: Gaussian Splatting with Few View Matching and Multi-stage Training
Subgraph Neural Networks
Online Normalization for Training Neural Networks
Dynamically Adaptable CMOS Winner-Take-All Neural Network
DEFT: Efficient Fine-tuning of Diffusion Models by Learning the Generalised $h$-transform
Learning the k in k-means
PERIA: Perceive, Reason, Imagine, Act via Holistic Language and Vision Planning for Manipulation
From Stochastic Mixability to Fast Rates
Optimal Change-Detection and Spiking Neurons
Off-Road Obstacle Avoidance through End-to-End Learning
Unlabeled Data Improves Adversarial Robustness
Reward-Free Model-Based Reinforcement Learning with Linear Function Approximation
Mismatched No More: Joint Model-Policy Optimization for Model-Based RL
4M: Massively Multimodal Masked Modeling
Octopus: A Multi-modal LLM with Parallel Recognition and Sequential Understanding
e-COP : Episodic Constrained Optimization of Policies
When Are Solutions Connected in Deep Networks?
Learning with the weighted trace-norm under arbitrary sampling distributions
MultiVENT: Multilingual Videos of Events and Aligned Natural Text
Neural Network Computation by In Vitro Transcriptional Circuits
Accurate Interpolation for Scattered Data through Hierarchical Residual Refinement
A PAC-Bayesian Margin Bound for Linear Classifiers: Why SVMs work
Emergence of heavy tails in homogenized stochastic gradient descent
Dueling Bandits with Team Comparisons
Change Event Dataset for Discovery from Spatio-temporal Remote Sensing Imagery
Using Free Energies to Represent Q-values in a Multiagent Reinforcement Learning Task
A Cortically-Plausible Inverse Problem Solving Method Applied to Recognizing Static and Kinematic 3D Objects
Robust Multi-Agent Reinforcement Learning via Adversarial Regularization: Theoretical Foundation and Stable Algorithms
Backpropagating Linearly Improves Transferability of Adversarial Examples
ReSync: Riemannian Subgradient-based Robust Rotation Synchronization
On the Statistical Consistency of Risk-Sensitive Bayesian Decision-Making
AOT: Appearance Optimal Transport Based Identity Swapping for Forgery Detection
Cell ontology guided transcriptome foundation model
Efficient Learning of Sparse Representations with an Energy-Based Model
Estimating Noise Transition Matrix with Label Correlations for Noisy Multi-Label Learning
Dualing GANs
Multimodular Architecture fir Remote Sensing Options
Isotropic Hashing
Diffusion-Reward Adversarial Imitation Learning
HuggingGPT: Solving AI Tasks with ChatGPT and its Friends in Hugging Face
Counter-Current Learning: A Biologically Plausible Dual Network Approach for Deep Learning
Community detection using fast low-cardinality semidefinite programming
K-LITE: Learning Transferable Visual Models with External Knowledge
Efficient Inference for Distributions on Permutations
A Bayesian Framework for Figure-Ground Interpretation
Learning Sparse Multiscale Image Representations
Statistical Guarantees for Variational Autoencoders using PAC-Bayesian Theory
Depth-First Proof-Number Search with Heuristic Edge Cost and Application to Chemical Synthesis Planning
Stochastic Network Design in Bidirected Trees
Simplicial Mixtures of Markov Chains: Distributed Modelling of Dynamic User Profiles
Randomized Algorithms for Comparison-based Search
TernGrad: Ternary Gradients to Reduce Communication in Distributed Deep Learning
Evaluation of Adaptive Mixtures of Competing Experts
Voicebox: Text-Guided Multilingual Universal Speech Generation at Scale
Asynchronous Coordinate Descent under More Realistic Assumptions
Learning Large Graph Property Prediction via Graph Segment Training
State-free Reinforcement Learning
Learning Goal-Conditioned Representations for Language Reward Models
Bringing Image Scene Structure to Video via Frame-Clip Consistency of Object Tokens
Efficient Offline Communication Policies for Factored Multiagent POMDPs
On the Complexity of Differentially Private Best-Arm Identification with Fixed Confidence
Randomized Sparse Neural Galerkin Schemes for Solving Evolution Equations with Deep Networks
Multi-Task Reinforcement Learning with Soft Modularization
Recovery of Sparse Probability Measures via Convex Programming
Online Learning of Non-stationary Sequences
Fitted Q-iteration in continuous action-space MDPs
HEDNet: A Hierarchical Encoder-Decoder Network for 3D Object Detection in Point Clouds
Large-Scale Sparsified Manifold Regularization
The Pick-to-Learn Algorithm: Empowering Compression for Tight Generalization Bounds and Improved Post-training Performance
Fast Bidirectional Probability Estimation in Markov Models
S2P: State-conditioned Image Synthesis for Data Augmentation in Offline Reinforcement Learning
Fair and Optimal Decision Trees: A Dynamic Programming Approach
Towards Hard-pose Virtual Try-on via 3D-aware Global Correspondence Learning
Scrambled Objects for Least-Squares Regression
Beyond the Best: Distribution Functional Estimation in Infinite-Armed Bandits
UE4-NeRF: Neural Radiance Field for Real-Time Rendering of Large-Scale Scene
VITA: Video Instance Segmentation via Object Token Association
Towards Reliable Simulation-Based Inference with Balanced Neural Ratio Estimation
"Lossless" Compression of Deep Neural Networks: A High-dimensional Neural Tangent Kernel Approach
On the Adaptive Properties of Decision Trees
Impact of an Energy Normalization Transform on the Performance of the LF-ASD Brain Computer Interface
Deep Recurrent Optimal Stopping
Look Ma, No Hands! Agent-Environment Factorization of Egocentric Videos
A Discriminative Latent Model of Image Region and Object Tag Correspondence
Invariance and Stability of Deep Convolutional Representations
Learn more, but bother less: parameter efficient continual learning
A Combinatorial Algorithm for the Semi-Discrete Optimal Transport Problem
NeuForm: Adaptive Overfitting for Neural Shape Editing
The decomposition of the higher-order homology embedding constructed from the $k$-Laplacian
A B-P ANN Commodity Trader
The Population Posterior and Bayesian Modeling on Streams
A consistently adaptive trust-region method
Weighted importance sampling for off-policy learning with linear function approximation
Compositional 3D-aware Video Generation with LLM Director
Zero-shot Image Editing with Reference Imitation
Bootstrap Your Own Latent - A New Approach to Self-Supervised Learning
Interpreting Learned Feedback Patterns in Large Language Models
Abstracted Shapes as Tokens - A Generalizable and Interpretable Model for Time-series Classification
Backpropagation with Callbacks: Foundations for Efficient and Expressive Differentiable Programming
Generated and Pseudo Content guided Prototype Refinement for Few-shot Point Cloud Segmentation
Renku: a platform for sustainable data science
Learning to Reason with Third Order Tensor Products
Fast Distance Oracles for Any Symmetric Norm
PrObeD: Proactive Object Detection Wrapper
Linking In-context Learning in Transformers to Human Episodic Memory
Convergence and Pattern-Stabilization in the Boltzmann Machine
Inverse Rational Control with Partially Observable Continuous Nonlinear Dynamics
Entrywise convergence of iterative methods for eigenproblems
Best of Both Worlds: Practical and Theoretically Optimal Submodular Maximization in Parallel
Asymmetric Certified Robustness via Feature-Convex Neural Networks
Distributed Learning of Conditional Quantiles in the Reproducing Kernel Hilbert Space
Sparse Flows: Pruning Continuous-depth Models
Information-theoretic lower bounds on the oracle complexity of convex optimization
Promoting Coordination through Policy Regularization in Multi-Agent Deep Reinforcement Learning
ODE-based Recurrent Model-free Reinforcement Learning for POMDPs
Temporal Low-Order Statistics of Natural Sounds
Towards a Standardised Performance Evaluation Protocol for Cooperative MARL
Coordinate Descent with Bandit Sampling
Active preference learning for ordering items in- and out-of-sample
Early Stage Convergence and Global Convergence of Training Mildly Parameterized Neural Networks
Comparing Beliefs, Surveys, and Random Walks
QueryPose: Sparse Multi-Person Pose Regression via Spatial-Aware Part-Level Query
Discriminative Transfer Learning with Tree-based Priors
Dance of SNN and ANN: Solving binding problem by combining spike timing and reconstructive attention
The Intelligent surfer: Probabilistic Combination of Link and Content Information in PageRank
Multi-view Subspace Clustering on Topological Manifold
Precision-Recall Divergence Optimization for Generative Modeling with GANs and Normalizing Flows
Equipping Experts/Bandits with Long-term Memory
An Artificial Neural Network for Spatio-Temporal Bipolar Patterns: Application to Phoneme Classification
RS-Del: Edit Distance Robustness Certificates for Sequence Classifiers via Randomized Deletion
SCRREAM : SCan, Register, REnder And Map: A Framework for Annotating Accurate and Dense 3D Indoor Scenes with a Benchmark
On the convergence of single-call stochastic extra-gradient methods
Approximating Posterior Distributions in Belief Networks Using Mixtures
Characterizing the Impacts of Semi-supervised Learning for Weak Supervision
Diffusion Models and Semi-Supervised Learners Benefit Mutually with Few Labels
Turbocharging Solution Concepts: Solving NEs, CEs and CCEs with Neural Equilibrium Solvers
Sorting with Predictions
Imitation Learning by Coaching
Geometric Exploitation for Indoor Panoramic Semantic Segmentation
InterCode: Standardizing and Benchmarking Interactive Coding with Execution Feedback
Stochastic Runge-Kutta Accelerates Langevin Monte Carlo and Beyond
Content-based Unrestricted Adversarial Attack
NanoFlow: Scalable Normalizing Flows with Sublinear Parameter Complexity
Learning Modulated Transformation in GANs
Modeling Worlds in Text
Robust Learning against Relational Adversaries
DivBO: Diversity-aware CASH for Ensemble Learning
Emergent Communication: Generalization and Overfitting in Lewis Games
Sharp Bounds for Generalized Uniformity Testing
Differentiable Meta-Learning of Bandit Policies
Learning To Count Objects in Images
Universal Neural Functionals
Information Maximization in Single Neurons
Making a (Counterfactual) Difference One Rationale at a Time
Tensor Subspace Analysis
Hierarchical Reinforcement Learning with Timed Subgoals
Dynamic Infinite Relational Model for Time-varying Relational Data Analysis
Stepping Forward on the Last Mile
Online Constrained Meta-Learning: Provable Guarantees for Generalization
Predicting the Geometry of Metal Binding Sites from Protein Sequence
Interaction Modeling with Multiplex Attention
Robust Offline Active Learning on Graphs
Fair Rank Aggregation
H-nobs: Achieving Certified Fairness and Robustness in Distributed Learning on Heterogeneous Datasets
Reward Finetuning for Faster and More Accurate Unsupervised Object Discovery
Analog LSI Implementation of an Auto-Adaptive Network for Real-Time Separation of Independent Signals
Controlling Continuous Relaxation for Combinatorial Optimization
TUSK: Task-Agnostic Unsupervised Keypoints
Label consistency in overfitted generalized $k$-means
Parametric Instance Classification for Unsupervised Visual Feature learning
A Maximum-Entropy Approach to Off-Policy Evaluation in Average-Reward MDPs
Perceiving Longer Sequences With Bi-Directional Cross-Attention Transformers
Cross-links Matter for Link Prediction: Rethinking the Debiased GNN from a Data Perspective
HardCore Generation: Generating Hard UNSAT Problems for Data Augmentation
Topographic VAEs learn Equivariant Capsules
Pretraining with Random Noise for Fast and Robust Learning without Weight Transport
Private Stochastic Convex Optimization with Heavy Tails: Near-Optimality from Simple Reductions
Fairness in Social Influence Maximization via Optimal Transport
The Reversible Residual Network: Backpropagation Without Storing Activations
The Neurodynamics of Belief Propagation on Binary Markov Random Fields
TexQ: Zero-shot Network Quantization with Texture Feature Distribution Calibration
Differentiable Analog Quantum Computing for Optimization and Control
Learning Loss for Test-Time Augmentation
Noether Networks: meta-learning useful conserved quantities
Gradient-based kernel method for feature extraction and variable selection
Trajectory Inference via Mean-field Langevin in Path Space
Bellman Residual Orthogonalization for Offline Reinforcement Learning
Who's asking? User personas and the mechanics of latent misalignment
How Re-sampling Helps for Long-Tail Learning?
MaskRNN: Instance Level Video Object Segmentation
SILENCE: Protecting privacy in offloaded speech understanding on resource-constrained devices
Adaptive whitening with fast gain modulation and slow synaptic plasticity
IKEA Manuals at Work: 4D Grounding of Assembly Instructions on Internet Videos
Bias in Evaluation Processes: An Optimization-Based Model
Neural Program Generation Modulo Static Analysis
Optimal Query Complexities for Dynamic Trace Estimation
Multi-Agent Common Knowledge Reinforcement Learning
Using epitomes to model genetic diversity: Rational design of HIV vaccines
Iterative Scene Graph Generation
MAgNet: Mesh Agnostic Neural PDE Solver
Certified Monotonic Neural Networks
Learning Body Pose via Specialized Maps
COFI RANK - Maximum Margin Matrix Factorization for Collaborative Ranking
Dynamic Structure Super-Resolution
Supermasks in Superposition
A fast heuristic to optimize time-space tradeoff for large models
Matrix Completion with Quantified Uncertainty through Low Rank Gaussian Copula
MixSeq: Connecting Macroscopic Time Series Forecasting with Microscopic Time Series Data
DELTA: Diverse Client Sampling for Fasting Federated Learning
On the Robustness of Removal-Based Feature Attributions
Pipeline Combinators for Gradual AutoML
t-divergence Based Approximate Inference
Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, NeurIPS 2023, New Orleans, LA, USA, December 10 - 16, 2023
BAST: Bayesian Additive Regression Spanning Trees for Complex Constrained Domain
Structured sparse coding via lateral inhibition
A Gaussian Tree Approximation for Integer Least-Squares
Adversarial Neuron Pruning Purifies Backdoored Deep Models
Ancestral Causal Inference
Hierarchical Topic Modeling for Analysis of Time-Evolving Personal Choices
Wasserstein Weisfeiler-Lehman Graph Kernels
Ultra Fast Medoid Identification via Correlated Sequential Halving
Neural Scene Flow Prior
Knowledge-Aware Bayesian Deep Topic Model
T-LoHo: A Bayesian Regularization Model for Structured Sparsity and Smoothness on Graphs
Multiple Instance Learning for Computer Aided Diagnosis
Supra-Laplacian Encoding for Transformer on Dynamic Graphs