yusuke1997/dblp-id-title huggingface dataset:
Unlocking Deterministic Robustness Certification on ImageNet
Skills Regularized Task Decomposition for Multi-task Offline Reinforcement Learning
From random walks to distances on unweighted graphs
Croissant: A Metadata Format for ML-Ready Datasets
Sharp Bounds for Generalized Causal Sensitivity Analysis
Exploring Behavior-Relevant and Disentangled Neural Dynamics with Generative Diffusion Models
Provable Model-based Nonlinear Bandit and Reinforcement Learning: Shelve Optimism, Embrace Virtual Curvature
PointGPT: Auto-regressively Generative Pre-training from Point Clouds
Large Margin Deep Networks for Classification
PALMER: Perception - Action Loop with Memory for Long-Horizon Planning
Do Finetti: On Causal Effects for Exchangeable Data
On the Optimality of Perturbations in Stochastic and Adversarial Multi-armed Bandit Problems
DF40: Toward Next-Generation Deepfake Detection
Representation Learning for Integrating Multi-domain Outcomes to Optimize Individualized Treatment
Ridge Rider: Finding Diverse Solutions by Following Eigenvectors of the Hessian
On Softmax Direct Preference Optimization for Recommendation
Modeling Overlapping Communities with Node Popularities
Near-optimal Regret Bounds for Reinforcement Learning
Articulate your NeRF: Unsupervised articulated object modeling via conditional view synthesis
Revisit Fuzzy Neural Network: Demystifying Batch Normalization and ReLU with Generalized Hamming Network
Improving Transfer Rates in Brain Computer Interfacing: A Case Study
Quantifying Learnability and Describability of Visual Concepts Emerging in Representation Learning
Hyperbolic Graph Convolutional Neural Networks
Counterfactual Predictions under Runtime Confounding
Glow: Generative Flow with Invertible 1x1 Convolutions
Kernel Feature Spaces and Nonlinear Blind Souce Separation
WildPPG: A Real-World PPG Dataset of Long Continuous Recordings
Neural Transmitted Radiance Fields
Learning and Collusion in Multi-unit Auctions
Fourier Amplitude and Correlation Loss: Beyond Using L2 Loss for Skillful Precipitation Nowcasting
FD-Align: Feature Discrimination Alignment for Fine-tuning Pre-Trained Models in Few-Shot Learning
Ranking annotators for crowdsourced labeling tasks
FedGTST: Boosting Global Transferability of Federated Models via Statistics Tuning
VALUE: A Multi-Task Benchmark for Video-and-Language Understanding Evaluation
ASPEN: Breaking Operator Barriers for Efficient Parallelization of Deep Neural Networks
Hidden Common Cause Relations in Relational Learning
Convergence of the Wake-Sleep Algorithm
Deep Diffusion-Invariant Wasserstein Distributional Classification
Monte-Carlo Planning in Large POMDPs
Real Robot Challenge 2022: Learning Dexterous Manipulation from Offline Data in the Real World
Robust Attribution Regularization
Single Transistor Learning Synapses
Tracr: Compiled Transformers as a Laboratory for Interpretability
LobsDICE: Offline Learning from Observation via Stationary Distribution Correction Estimation
Bypass Exponential Time Preprocessing: Fast Neural Network Training via Weight-Data Correlation Preprocessing
Shape from Blur: Recovering Textured 3D Shape and Motion of Fast Moving Objects
Hardware-adaptive Efficient Latency Prediction for NAS via Meta-Learning
Entropic Desired Dynamics for Intrinsic Control
Private and Non-private Uniformity Testing for Ranking Data
Maximum Margin Interval Trees
Policy Optimization in Adversarial MDPs: Improved Exploration via Dilated Bonuses
Universality and individuality in neural dynamics across large populations of recurrent networks
Unified Domain Generalization and Adaptation for Multi-View 3D Object Detection
Optimal Regret Minimization in Posted-Price Auctions with Strategic Buyers
Learning Stochastic Inverses
Conditional Visual Tracking in Kernel Space
Group Sparse Coding with a Laplacian Scale Mixture Prior
GAVEL: Generating Games via Evolution and Language Models
Scalable Optimization in the Modular Norm
Gamma-Models: Generative Temporal Difference Learning for Infinite-Horizon Prediction
Odor Encoding by the Olfactory System - from Biology to a Receptorless Artificial Nose
Web-Scale Visual Entity Recognition: An LLM-Driven Data Approach
Unsupervised Learning of Shape Programs with Repeatable Implicit Parts
Sparse and Continuous Attention Mechanisms
Human Active Learning
Exploring Social Posterior Collapse in Variational Autoencoder for Interaction Modeling
Calibrating Predictions to Decisions: A Novel Approach to Multi-Class Calibration
Size Matters: Metric Visual Search Constraints from Monocular Metadata
Learnability with Indirect Supervision Signals
On Translation and Reconstruction Guarantees of the Cycle-Consistent Generative Adversarial Networks
Multilingual Abusive Comment Detection at Scale for Indic Languages
A Natural Policy Gradient
Deep Reinforcement Learning in a Handful of Trials using Probabilistic Dynamics Models
Learning Recourse on Instance Environment to Enhance Prediction Accuracy
LCM: Locally Constrained Compact Point Cloud Model for Masked Point Modeling
Facing Off World Model Backbones: RNNs, Transformers, and S4
Novel Object Synthesis via Adaptive Text-Image Harmony
Revisiting Out-of-distribution Robustness in NLP: Benchmarks, Analysis, and LLMs Evaluations
Reinforcement Learning Predicts the Site of Plasticity for Auditory Remapping in the Barn Owl
Distilling Image Classifiers in Object Detectors
Distributional Gradient Matching for Learning Uncertain Neural Dynamics Models
Beyond Grids: Learning Graph Representations for Visual Recognition
A Separation in Heavy-Tailed Sampling: Gaussian vs. Stable Oracles for Proximal Samplers
Accelerating Monte Carlo Tree Search with Probability Tree State Abstraction
Invariance and identifiability issues for word embeddings
Learning Mixture of Gaussians with Streaming Data
Learning to Reason via Program Generation, Emulation, and Search
Spectral Hashing
Look Beneath the Surface: Exploiting Fundamental Symmetry for Sample-Efficient Offline RL
Learning to Reconstruct Shapes from Unseen Classes
Some Estimates on the Number of Connections and Hidden Units for Feed-Forward Networks
Analyzing Data-Centric Properties for Graph Contrastive Learning
Dual-frame Fluid Motion Estimation with Test-time Optimization and Zero-divergence Loss
The Implicit Bias of Gradient Descent toward Collaboration between Layers: A Dynamic Analysis of Multilayer Perceptions
STAR-Caps: Capsule Networks with Straight-Through Attentive Routing
Focus Your Attention when Few-Shot Classification
MoCoDA: Model-based Counterfactual Data Augmentation
NuTrea: Neural Tree Search for Context-guided Multi-hop KGQA
Adaptive Back-Propagation in On-Line Learning of Multilayer Networks
Cross-Language Aphasia Detection using Optimal Transport Domain Adaptation
Combinatorial Bayesian Optimization using the Graph Cartesian Product
FLIP: Benchmark tasks in fitness landscape inference for proteins
Normalized Spectral Map Synchronization
Segment Anything without Supervision
Generalization Bounds For Meta-Learning: An Information-Theoretic Analysis
Leveraging partial stragglers within gradient coding
SnapFusion: Text-to-Image Diffusion Model on Mobile Devices within Two Seconds
Glow-TTS: A Generative Flow for Text-to-Speech via Monotonic Alignment Search
A hybrid sampler for Poisson-Kingman mixture models
Surprising Instabilities in Training Deep Networks and a Theoretical Analysis
Classification Accuracy Score for Conditional Generative Models
Streaming Detection of Queried Event Start
Mobilizing Personalized Federated Learning in Infrastructure-Less and Heterogeneous Environments via Random Walk Stochastic ADMM
UnModNet: Learning to Unwrap a Modulo Image for High Dynamic Range Imaging
Markov Equivalence and Consistency in Differentiable Structure Learning
Which priors matter? Benchmarking models for learning latent dynamics
Gaussian Process Priors with Uncertain Inputs - Application to Multiple-Step Ahead Time Series Forecasting
Probabilistic Attention for Interactive Segmentation
Initializing Variable-sized Vision Transformers from Learngene with Learnable Transformation
The Convolution Exponential and Generalized Sylvester Flows
Disentangling the Roles of Distinct Cell Classes with Cell-Type Dynamical Systems
The Minority Matters: A Diversity-Promoting Collaborative Metric Learning Algorithm
Scalable Algorithms for String Kernels with Inexact Matching
Stochastic Shared Embeddings: Data-driven Regularization of Embedding Layers
IR-CM: The Fast and General-purpose Image Restoration Method Based on Consistency Model
Financial Applications of Learning from Hints
Classification of Multi-Spectral Pixels by the Binary Diamond Neural Network
Lethal Dose Conjecture on Data Poisoning
FAST: A Dual-tier Few-Shot Learning Paradigm for Whole Slide Image Classification
QuadMamba: Learning Quadtree-based Selective Scan for Visual State Space Model
Isometric 3D Adversarial Examples in the Physical World
Bayesian Inference of Individualized Treatment Effects using Multi-task Gaussian Processes
Adaptive Synchronization of Neural and Physical Oscillators
Finite-Time Analysis of Round-Robin Kullback-Leibler Upper Confidence Bounds for Optimal Adaptive Allocation with Multiple Plays and Markovian Rewards
EEG-GRAPH: A Factor-Graph-Based Model for Capturing Spatial, Temporal, and Observational Relationships in Electroencephalograms
Log-Hilbert-Schmidt metric between positive definite operators on Hilbert spaces
SlotDiffusion: Object-Centric Generative Modeling with Diffusion Models
Covariance-Controlled Adaptive Langevin Thermostat for Large-Scale Bayesian Sampling
Paraphrase Generation with Latent Bag of Words
A Massively Parallel Self-Tuning Context-Free Parser
JANUS: Speech-to-Speech Translation Using Connectionist and Non-Connectionist Techniques
Extracting Rules from Artifical Neural Networks with Distributed Representations
An Analog VLSI Chip for Thin-Plate Surface Interpolation
Biological key-value memory networks
Pruning has a disparate impact on model accuracy
MosaicBERT: A Bidirectional Encoder Optimized for Fast Pretraining
Communication-efficient SGD: From Local SGD to One-Shot Averaging
Identification of Conditional Causal Effects under Markov Equivalence
Deep Multimodal Fusion by Channel Exchanging
Kernel Hyperalignment
Sample Complexity of Episodic Fixed-Horizon Reinforcement Learning
Dual-Perspective Activation: Efficient Channel Denoising via Joint Forward-Backward Criterion for Artificial Neural Networks
Post-Hoc Reversal: Are We Selecting Models Prematurely?
Advances in Neural Information Processing Systems 7, [NIPS Conference, Denver, Colorado, USA, 1994]
Ensuring Fairness Beyond the Training Data
Speeding up Permutation Testing in Neuroimaging
On the Convergence and Robustness of Training GANs with Regularized Optimal Transport
Stochastic Mixed-Signal VLSI Architecture for High-Dimensional Kernel Machines
Configuration Estimates Improve Pedestrian Finding
Revisiting Model Stitching to Compare Neural Representations
Scalable Levy Process Priors for Spectral Kernel Learning
Provably Faster Algorithms for Bilevel Optimization via Without-Replacement Sampling
Third-Person Visual Imitation Learning via Decoupled Hierarchical Controller
Sharp uniform convergence bounds through empirical centralization
VidMan: Exploiting Implicit Dynamics from Video Diffusion Model for Effective Robot Manipulation
Unique sparse decomposition of low rank matrices
A Hierarchical Model of Complex Cells in Visual Cortex for the Binocular Perception of Motion-in-Depth
Non-normal Recurrent Neural Network (nnRNN): learning long time dependencies while improving expressivity with transient dynamics
Fast geometric learning with symbolic matrices
Orthogonal Matching Pursuit with Replacement
DYffusion: A Dynamics-informed Diffusion Model for Spatiotemporal Forecasting
Universal Online Convex Optimization with 1 Projection per Round
Learning Transferable Adversarial Perturbations
The Causality for Climate Competition
Improved Bayes Regret Bounds for Multi-Task Hierarchical Bayesian Bandit Algorithms
A Practical Monte Carlo Implementation of Bayesian Learning
Understanding Hallucinations in Diffusion Models through Mode Interpolation
A Unified Framework for 3D Scene Understanding
AutoST: Towards the Universal Modeling of Spatio-temporal Sequences
Analyzing the Confidentiality of Undistillable Teachers in Knowledge Distillation
An Analog Visual Pre-Processing Processor Employing Cyclic Line Access in Only-Nearest-Neighbor-Interconnects Architecture
Cascading Contextual Assortment Bandits
Multi-armed Bandits: Competing with Optimal Sequences
Munchausen Reinforcement Learning
Learning Trajectories are Generalization Indicators
ReST-MCTS*: LLM Self-Training via Process Reward Guided Tree Search
The People's Speech: A Large-Scale Diverse English Speech Recognition Dataset for Commercial Usage
On the Convergence of the Concave-Convex Procedure
Reinforcement Learning in Continuous Action Spaces through Sequential Monte Carlo Methods
Symbolic Opportunistic Policy Iteration for Factored-Action MDPs
Time-MMD: Multi-Domain Multimodal Dataset for Time Series Analysis
A Dirichlet Mixture Model of Hawkes Processes for Event Sequence Clustering
Connectionist Music Composition Based on Melodic and Stylistic Constraints
Diversified Recommendations for Agents with Adaptive Preferences
Faster Neural Network Training with Approximate Tensor Operations
A Projection-free Algorithm for Constrained Stochastic Multi-level Composition Optimization
Structured State Space Models for In-Context Reinforcement Learning
A Feature Selection Algorithm Based on the Global Minimization of a Generalization Error Bound
Human Face Detection in Visual Scenes
Learning Neural Implicit through Volume Rendering with Attentive Depth Fusion Priors
A Rigorous Analysis of Linsker-Type Hebbian Learning
Spatial Transformer Networks
Slow and Weak Attractor Computation Embedded in Fast and Strong E-I Balanced Neural Dynamics
The Asymptotic Convergence-Rate of Q-learning
SSUL: Semantic Segmentation with Unknown Label for Exemplar-based Class-Incremental Learning
Stability-Based Model Selection
Large-Scale Unsupervised Object Discovery
Model-Based Episodic Memory Induces Dynamic Hybrid Controls
MADG: Margin-based Adversarial Learning for Domain Generalization
Domain Generalization for Medical Imaging Classification with Linear-Dependency Regularization
Learning Curves for Deep Structured Gaussian Feature Models
Diffusion Spectral Representation for Reinforcement Learning
Attention as Implicit Structural Inference
Modeling Clutter Perception using Parametric Proto-object Partitioning
Dataset Distillation using Neural Feature Regression
How Fine-Tuning Allows for Effective Meta-Learning
EM Optimization of Latent-Variables Density Models
Reinforcement Learning with Feedback Graphs
Optimal Algorithms for Continuous Non-monotone Submodular and DR-Submodular Maximization
Can Language Models Solve Graph Problems in Natural Language?
Mixture of time-warped trajectory models for movement decoding
WildfireSpreadTS: A dataset of multi-modal time series for wildfire spread prediction
Redundancy and Dimensionality Reduction in Sparse-Distributed Representations of Natural Objects in Terms of Their Local Features
Relaxed Marginal Consistency for Differentially Private Query Answering
Estimation with Norm Regularization
Near-Optimal Comparison Based Clustering
A Dataset for Analyzing Streaming Media Performance over HTTP/3 Browsers
A Linearly Convergent Proximal Gradient Algorithm for Decentralized Optimization
Trust Region-Based Safe Distributional Reinforcement Learning for Multiple Constraints
Addressing the speed-accuracy simulation trade-off for adaptive spiking neurons
SInGE: Sparsity via Integrated Gradients Estimation of Neuron Relevance
Voila-A: Aligning Vision-Language Models with User's Gaze Attention
Unsupervised On-line Learning of Decision Trees for Hierarchical Data Analysis
Active Surrogate Estimators: An Active Learning Approach to Label-Efficient Model Evaluation
Machine Learning and Interpretation in Neuroimaging - 4th International Workshop, MLINI 2014, Held at NIPS 2014, Montreal, QC, Canada, December 13, 2014, Revised Selected Papers
Kernel Interpolation with Sparse Grids
Unsupervised Learning of Visual Sense Models for Polysemous Words
Efficient Loss-Based Decoding on Graphs for Extreme Classification
Dynamic Visual Reasoning by Learning Differentiable Physics Models from Video and Language
Matrix encoding networks for neural combinatorial optimization
Input-Cell Attention Reduces Vanishing Saliency of Recurrent Neural Networks
Generative Adversarial Nets
Efficient Kernel Discriminant Analysis via QR Decomposition
Fast Rates to Bayes for Kernel Machines
Artistic Style Transfer with Internal-external Learning and Contrastive Learning
Logarithmic Regret from Sublinear Hints
A Consistent and Differentiable Lp Canonical Calibration Error Estimator
A Contour Stochastic Gradient Langevin Dynamics Algorithm for Simulations of Multi-modal Distributions
Tell What You Hear From What You See - Video to Audio Generation Through Text
A graph-theoretic approach to multitasking
SPERT-II: A Vector Microprocessor System and its Application to Large Problems in Backpropagation Training
Projected Stein Variational Gradient Descent
Fast T2T: Optimization Consistency Speeds Up Diffusion-Based Training-to-Testing Solving for Combinatorial Optimization
Better by default: Strong pre-tuned MLPs and boosted trees on tabular data
Digraph Inception Convolutional Networks
Resetting the Optimizer in Deep RL: An Empirical Study
ECLipsE: Efficient Compositional Lipschitz Constant Estimation for Deep Neural Networks
Birder: Communication-Efficient 1-bit Adaptive Optimizer for Practical Distributed DNN Training
Batch Bayesian optimisation via density-ratio estimation with guarantees
An Improved Analysis of (Variance-Reduced) Policy Gradient and Natural Policy Gradient Methods
Bayesian model learning in human visual perception
Segment Any Point Cloud Sequences by Distilling Vision Foundation Models
Preserved central model for faster bidirectional compression in distributed settings
A Regret-Variance Trade-Off in Online Learning
Achieving Domain-Independent Certified Robustness via Knowledge Continuity
Incorporating Test Inputs into Learning
Efficient Low Rank Gaussian Variational Inference for Neural Networks
Unsupervised Anomaly Detection in The Presence of Missing Values
Parameter-Efficient Masking Networks
A Near-Optimal Primal-Dual Method for Off-Policy Learning in CMDP
Learning-Augmented Dynamic Power Management with Multiple States via New Ski Rental Bounds
Consistency of weighted majority votes
Training fMRI Classifiers to Discriminate Cognitive States across Multiple Subjects
Improving neural network representations using human similarity judgments
Expectation-Maximization for Learning Determinantal Point Processes
Safe Policy Improvement by Minimizing Robust Baseline Regret
Unsupervised Video Object Segmentation for Deep Reinforcement Learning
Probability Estimates for Multi-Class Classification by Pairwise Coupling
DistrictNet: Decision-aware learning for geographical districting
Scalable Bayesian inference of dendritic voltage via spatiotemporal recurrent state space models
Transportability for Bandits with Data from Different Environments
MVSDet: Multi-View Indoor 3D Object Detection via Efficient Plane Sweeps
Relaxing Local Robustness
Stochastic Frank-Wolfe for Composite Convex Minimization
No Regrets: Investigating and Improving Regret Approximations for Curriculum Discovery
Approximate Planning in POMDPs with Macro-Actions
On the Expressive Power of Tree-Structured Probabilistic Circuits
Local plasticity rules can learn deep representations using self-supervised contrastive predictions
Subspace-Based Face Recognition in Analog VLSI
Real-Time Recurrent Learning using Trace Units in Reinforcement Learning
Linear Time Computation of Moments in Sum-Product Networks
Multi-Objective Non-parametric Sequential Prediction
Machine Teaching for Bayesian Learners in the Exponential Family
Showing versus doing: Teaching by demonstration
Neural Manifold Ordinary Differential Equations
Learning to Predict Without Looking Ahead: World Models Without Forward Prediction
Uncoupled and Convergent Learning in Two-Player Zero-Sum Markov Games with Bandit Feedback
MedJourney: Benchmark and Evaluation of Large Language Models over Patient Clinical Journey
Flexible mean field variational inference using mixtures of non-overlapping exponential families
Fast and Accurate Inference of Plackett-Luce Models
Situated Grounding Facilitates Multimodal Concept Learning for AI
Conditional Independence Testing using Generative Adversarial Networks
Described Object Detection: Liberating Object Detection with Flexible Expressions
Image Captioners Are Scalable Vision Learners Too
A Topological Filter for Learning with Label Noise
Nearly Optimal Algorithms for Linear Contextual Bandits with Adversarial Corruptions
Exponential Graph is Provably Efficient for Decentralized Deep Training
End-to-end Differentiable Proving
Interpretable Mesomorphic Networks for Tabular Data
The Role of Activity in Synaptic Competition at the Neuromuscular Junction
Improved Expressivity Through Dendritic Neural Networks
A Neural Autoregressive Topic Model
ResoNet: Noise-Trained Physics-Informed MRI Off-Resonance Correction
Stochastic Kernel Regularisation Improves Generalisation in Deep Kernel Machines
Cascade RPN: Delving into High-Quality Region Proposal Network with Adaptive Convolution
Local Signal Adaptivity: Provable Feature Learning in Neural Networks Beyond Kernels
Playing Pinball with non-invasive BCI
Partially Observed Maximum Entropy Discrimination Markov Networks
Reading Relevant Feature from Global Representation Memory for Visual Object Tracking
Evaluating Copyright Takedown Methods for Language Models
VAE Learning via Stein Variational Gradient Descent
Curriculum Offline Imitating Learning
Fast Algorithms for Large-State-Space HMMs with Applications to Web Usage Analysis
Video-based Human-Object Interaction Detection from Tubelet Tokens
Personalized Federated Learning With Gaussian Processes
Two is better than one: distinct roles for familiarity and recollection in retrieving palimpsest memories
On gradient regularizers for MMD GANs
Sparsity-Agnostic Linear Bandits with Adaptive Adversaries
Structuring Representations Using Group Invariants
SafeSora: Towards Safety Alignment of Text2Video Generation via a Human Preference Dataset
General Transportability of Soft Interventions: Completeness Results
On Joint Learning for Solving Placement and Routing in Chip Design
ImageNet-Hard: The Hardest Images Remaining from a Study of the Power of Zoom and Spatial Biases in Image Classification
Smoothness Matrices Beat Smoothness Constants: Better Communication Compression Techniques for Distributed Optimization
Synthetic Combinations: A Causal Inference Framework for Combinatorial Interventions
Randomized Sketches for Clustering: Fast and Optimal Kernel $k$-Means
SLaM: Student-Label Mixing for Distillation with Unlabeled Examples
An Optimality Principle for Unsupervised Learning
Recurrent linear models of simultaneously-recorded neural populations
Paloma: A Benchmark for Evaluating Language Model Fit
The Manifold Tangent Classifier
Rules and Similarity in Concept Learning
On Learning Domain-Invariant Representations for Transfer Learning with Multiple Sources
Maximum Likelihood Training of Score-Based Diffusion Models
Rewarded soups: towards Pareto-optimal alignment by interpolating weights fine-tuned on diverse rewards
Can You Learn an Algorithm? Generalizing from Easy to Hard Problems with Recurrent Networks
Globally Optimal Learning for Structured Elliptical Losses
On Optimal Robustness to Adversarial Corruption in Online Decision Problems
Unified 3D Segmenter As Prototypical Classifiers
Vaccine: Perturbation-aware Alignment for Large Language Models against Harmful Fine-tuning Attack
Generalization Error Bounds on Deep Learning with Markov Datasets
The Rank-Reduced Kalman Filter: Approximate Dynamical-Low-Rank Filtering In High Dimensions
Towards Accurate and Fair Cognitive Diagnosis via Monotonic Data Augmentation
Prediction on Spike Data Using Kernel Algorithms
A selective attention multi--chip system with dynamic synapses and spiking neurons