yusuke1997/dblp-id-title huggingface dataset:
MCUFormer: Deploying Vision Tranformers on Microcontrollers with Limited Memory
Towards Property-Based Classification of Clustering Paradigms
Parameter-Free Online Learning via Model Selection
Tight Sample Complexity of Large-Margin Learning
Biologically plausible solutions for spiking networks with efficient coding
Recovering Intrinsic Images from a Single Image
A Linear Programming Approach to Novelty Detection
Learning to Incentivize Other Learning Agents
Birth of a Transformer: A Memory Viewpoint
Pushing the limits of RNN Compression
Error Correcting Output Codes Improve Probability Estimation and Adversarial Robustness of Deep Neural Networks
Learning transport operators for image manifolds
Linear Transformers are Versatile In-Context Learners
Is Input Sparsity Time Possible for Kernel Low-Rank Approximation?
Generalized Linear Bandits with Limited Adaptivity
BLOX: Macro Neural Architecture Search Benchmark and Algorithms
KALE Flow: A Relaxed KL Gradient Flow for Probabilities with Disjoint Support
Local Minimax Complexity of Stochastic Convex Optimization
Towards Learning Universal Hyperparameter Optimizers with Transformers
CamoPatch: An Evolutionary Strategy for Generating Camoflauged Adversarial Patches
MaskLLM: Learnable Semi-Structured Sparsity for Large Language Models
Practical Variational Inference for Neural Networks
DeeR-VLA: Dynamic Inference of Multimodal Large Language Models for Efficient Robot Execution
Efficient and Local Parallel Random Walks
Low-Rank Subspaces in GANs
Bayesian Color Constancy with Non-Gaussian Models
Cross-Scale MAE: A Tale of Multiscale Exploitation in Remote Sensing
Estimating High Order Gradients of the Data Distribution by Denoising
On the Convergence of CART under Sufficient Impurity Decrease Condition
Supervised learning from incomplete data via an EM approach
The Cells Out of Sample (COOS) dataset and benchmarks for measuring out-of-sample generalization of image classifiers
Relational Verification Leaps Forward with RABBit
Bayesian Risk Markov Decision Processes
On Uniform Convergence and Low-Norm Interpolation Learning
MarginGAN: Adversarial Training in Semi-Supervised Learning
An Adaptive Deep RL Method for Non-Stationary Environments with Piecewise Stable Context
Transcoders find interpretable LLM feature circuits
Active Learning for Misspecified Models
SUPA: A Lightweight Diagnostic Simulator for Machine Learning in Particle Physics
Error-Minimizing Estimates and Universal Entry-Wise Error Bounds for Low-Rank Matrix Completion
Learning Visual Prior via Generative Pre-Training
Therapeutics Data Commons: Machine Learning Datasets and Tasks for Drug Discovery and Development
Robust Nonparametric Regression with Metric-Space Valued Output
Symplectic Adjoint Method for Exact Gradient of Neural ODE with Minimal Memory
Variational Bayes on Monte Carlo Steroids
Momentum Centering and Asynchronous Update for Adaptive Gradient Methods
MAP Estimation for Graphical Models by Likelihood Maximization
Token-Scaled Logit Distillation for Ternary Weight Generative Language Models
A Consistency-Aware Spot-Guided Transformer for Versatile and Hierarchical Point Cloud Registration
Delay-Tolerant Algorithms for Asynchronous Distributed Online Learning
Shapeshifter: a Parameter-efficient Transformer using Factorized Reshaped Matrices
Graph Transformer Networks
Localization with Sampling-Argmax
Multi-dataset Training of Transformers for Robust Action Recognition
Beyond Convexity: Stochastic Quasi-Convex Optimization
Design and Implementation of a High Speed CMAC Neural Network
WindsorML: High-Fidelity Computational Fluid Dynamics Dataset For Automotive Aerodynamics
Learning Fractional White Noises in Neural Stochastic Differential Equations
Optimal Best Markovian Arm Identification with Fixed Confidence
Efficient $\Phi$-Regret Minimization with Low-Degree Swap Deviations in Extensive-Form Games
A Dynamic HMM for On-line Segmentation of Sequential Data
A Differential Semantics for Jointree Algorithms
Semi-Supervised Support Vector Machines
ATOM3D: Tasks on Molecules in Three Dimensions
Object-Centric Representation Learning with Generative Spatial-Temporal Factorization
Fast Kernels for String and Tree Matching
Exponential Family PCA for Belief Compression in POMDPs
NSNet: A General Neural Probabilistic Framework for Satisfiability Problems
Entropic Causal Inference: Identifiability and Finite Sample Results
Online Matrix Completion with Side Information
Multi-Agent Reinforcement Learning is a Sequence Modeling Problem
A Game Theoretic Approach to Class-wise Selective Rationalization
GADBench: Revisiting and Benchmarking Supervised Graph Anomaly Detection
Who's Gaming the System? A Causally-Motivated Approach for Detecting Strategic Adaptation
Scalable nonconvex inexact proximal splitting
An efficient nonconvex reformulation of stagewise convex optimization problems
Learning annotated hierarchies from relational data
Transfer Learning by Borrowing Examples for Multiclass Object Detection
Protein-Nucleic Acid Complex Modeling with Frame Averaging Transformer
Spike-driven Transformer
MV2Cyl: Reconstructing 3D Extrusion Cylinders from Multi-View Images
Mining the Benefits of Two-stage and One-stage HOI Detection
TOIST: Task Oriented Instance Segmentation Transformer with Noun-Pronoun Distillation
A Novel Approach for Effective Multi-View Clustering with Information-Theoretic Perspective
OAM-TCD: A globally diverse dataset of high-resolution tree cover maps
A Kernelised Stein Statistic for Assessing Implicit Generative Models
Beyond Not-Forgetting: Continual Learning with Backward Knowledge Transfer
A Cortico-Cerebellar Model that Learns to Generate Distributed Motor Commands to Control a Kinematic Arm
TEG-DB: A Comprehensive Dataset and Benchmark of Textual-Edge Graphs
Fine-grained Analysis of In-context Linear Estimation: Data, Architecture, and Beyond
Ranking on Data Manifolds
Asymmetric Shapley values: incorporating causal knowledge into model-agnostic explainability
Deep Non-line-of-sight Imaging from Under-scanning Measurements
Forging The Graphs: A Low Rank and Positive Semidefinite Graph Learning Approach
Optimal and Approximate Adaptive Stochastic Quantization
Uniqueness of Belief Propagation on Signed Graphs
Agnostic Active Learning Without Constraints
Handling correlated and repeated measurements with the smoothed multivariate square-root Lasso
Scene Graph Generation with Role-Playing Large Language Models
Replay-and-Forget-Free Graph Class-Incremental Learning: A Task Profiling and Prompting Approach
Memory-Based Methods for Regression and Classification
Replay-Guided Adversarial Environment Design
Weak-shot Semantic Segmentation via Dual Similarity Transfer
Improved guarantees and a multiple-descent curve for Column Subset Selection and the Nystrom method
Predicting Cellular Responses to Novel Drug Perturbations at a Single-Cell Resolution
VidLanKD: Improving Language Understanding via Video-Distilled Knowledge Transfer
A Multi-Batch L-BFGS Method for Machine Learning
Overfitting in Neural Nets: Backpropagation, Conjugate Gradient, and Early Stopping
CoNSoLe: Convex Neural Symbolic Learning
Neural Isometries: Taming Transformations for Equivariant ML
Policy Gradient for Rectangular Robust Markov Decision Processes
Robust Conditional Probabilities
Regularized Off-Policy TD-Learning
DifNet: Semantic Segmentation by Diffusion Networks
Generalization Bounds and Consistency for Latent Structural Probit and Ramp Loss
Statistical, Robustness, and Computational Guarantees for Sliced Wasserstein Distances
Hierarchical Non-linear Factor Analysis and Topographic Maps
Information-Theoretic GAN Compression with Variational Energy-based Model
Leaning by Combining Memorization and Gradient Descent
A Reduction from Apprenticeship Learning to Classification
On the Power of Louvain in the Stochastic Block Model
Kernels and learning curves for Gaussian process regression on random graphs
Contrastive Graph Structure Learning via Information Bottleneck for Recommendation
Discriminative Network Models of Schizophrenia
Information-Geometrical Significance of Sparsity in Gallager Codes
HEST-1k: A Dataset For Spatial Transcriptomics and Histology Image Analysis
Change point detection and inference in multivariate non-parametric models under mixing conditions
Sliding Window and Pseudo-labeling techniques for Cellular Segmentation
Visual gesture-based robot guidance with a modular neural system
Label Poisoning is All You Need
Repeat Until Bored: A Pattern Selection Strategy
A Variational Principle for Model-based Morphing
On Spectral Clustering: Analysis and an algorithm
Non-Euclidean Universal Approximation
The Benefits of Balance: From Information Projections to Variance Reduction
Learning to Poke by Poking: Experiential Learning of Intuitive Physics
Data-Efficient Hierarchical Reinforcement Learning
Collective Oscillations in the Visual Cortex
Using Helmholtz Machines to Analyze Multi-channel Neuronal Recordings
End-To-End Memory Networks
Towards Croppable Implicit Neural Representations
Learning with Pseudo-Ensembles
RSA: Resolving Scale Ambiguities in Monocular Depth Estimators through Language Descriptions
Automated Hierarchy Discovery for Planning in Partially Observable Environments
From Speech Recognition to Spoken Language Understanding
Fast Prediction on a Tree
Infinite Time Horizon Safety of Bayesian Neural Networks
Robust Multi-Agent Reinforcement Learning with Model Uncertainty
Provable Subspace Clustering: When LRR meets SSC
Context-sensitive active sensing in humans
List-Decodable Mean Estimation via Iterative Multi-Filtering
TFGDA: Exploring Topology and Feature Alignment in Semi-supervised Graph Domain Adaptation through Robust Clustering
RepPoints v2: Verification Meets Regression for Object Detection
NAS-X: Neural Adaptive Smoothing via Twisting
Open Compound Domain Adaptation with Object Style Compensation for Semantic Segmentation
The PAIR-R24M Dataset for Multi-animal 3D Pose Estimation
Self-organization using synaptic plasticity
Differentiable Spike: Rethinking Gradient-Descent for Training Spiking Neural Networks
Information theoretic limits of learning a sparse rule
Langevin Dynamics with Continuous Tempering for Training Deep Neural Networks
Benign Underfitting of Stochastic Gradient Descent
On preserving non-discrimination when combining expert advice
Fast, Large-Scale Transformation-Invariant Clustering
Kullback-Leibler Proximal Variational Inference
Near-linear time approximation algorithms for optimal transport via Sinkhorn iteration
Learning to Sample and Aggregate: Few-shot Reasoning over Temporal Knowledge Graphs
Regularization-Free Estimation in Trace Regression with Symmetric Positive Semidefinite Matrices
Evaluating Post-hoc Explanations for Graph Neural Networks via Robustness Analysis
TuneTables: Context Optimization for Scalable Prior-Data Fitted Networks
Towards Combating Frequency Simplicity-biased Learning for Domain Generalization
Learning from Infinite Data in Finite Time
Practical Bayesian Optimization for Model Fitting with Bayesian Adaptive Direct Search
Generalization Bound of Gradient Descent for Non-Convex Metric Learning
Deep Evidential Regression
Rounding-based Moves for Metric Labeling
Flow-Attention-based Spatio-Temporal Aggregation Network for 3D Mask Detection
Nonparametric Bayesian Lomax delegate racing for survival analysis with competing risks
For high-dimensional hierarchical models, consider exchangeability of effects across covariates instead of across datasets
Enabling Detailed Action Recognition Evaluation Through Video Dataset Augmentation
Links Between Markov Models and Multilayer Perceptrons
Are You Talking to a Machine? Dataset and Methods for Multilingual Image Question
Diplomat: A Dialogue Dataset for Situated PragMATic Reasoning
An Investigation into Whitening Loss for Self-supervised Learning
A Mathematical Programming Approach to the Kernel Fisher Algorithm
Convergence Properties of the K-Means Algorithms
RCDN: Towards Robust Camera-Insensitivity Collaborative Perception via Dynamic Feature-based 3D Neural Modeling
Permutation Complexity Bound on Out-Sample Error
DynaDojo: An Extensible Platform for Benchmarking Scaling in Dynamical System Identification
Learning From Weakly Supervised Data by The Expectation Loss SVM (e-SVM) algorithm
A Neural Network Model of Naive Preference and Filial Imprinting in the Domestic Chick
Large Margin Component Analysis
Active Estimation of F-Measures
Distributed Submodular Cover: Succinctly Summarizing Massive Data
Automatic Symmetry Discovery with Lie Algebra Convolutional Network
Approximation and Convergence Properties of Generative Adversarial Learning
Euclidean distance compression via deep random features
Generative versus discriminative training of RBMs for classification of fMRI images
Unsupervised Skill Discovery via Recurrent Skill Training
Multiplication-Free Transformer Training via Piecewise Affine Operations
Understanding Linear Probing then Fine-tuning Language Models from NTK Perspective
Automated Multi-level Preference for MLLMs
TabMT: Generating tabular data with masked transformers
Moreau-Yosida Regularization for Grouped Tree Structure Learning
Triple Generative Adversarial Nets
Where are we in the search for an Artificial Visual Cortex for Embodied Intelligence?
Generalized DataWeighting via Class-Level Gradient Manipulation
Bullying10K: A Large-Scale Neuromorphic Dataset towards Privacy-Preserving Bullying Recognition
GRANOLA: Adaptive Normalization for Graph Neural Networks
Adaptive Domain Learning for Cross-domain Image Denoising
Enhancing Protein Mutation Effect Prediction through a Retrieval-Augmented Framework
Beyond Pinball Loss: Quantile Methods for Calibrated Uncertainty Quantification
NaturalProofs: Mathematical Theorem Proving in Natural Language
KeSpeech: An Open Source Speech Dataset of Mandarin and Its Eight Subdialects
Selecting the State-Representation in Reinforcement Learning
Dynamic Network Surgery for Efficient DNNs
Exploring the Algorithm-Dependent Generalization of AUPRC Optimization with List Stability
Causal Imitation Learning With Unobserved Confounders
On Tracking The Partition Function
Decentralized Randomly Distributed Multi-agent Multi-armed Bandit with Heterogeneous Rewards
Learning Debiased Classifier with Biased Committee
Quantum Algorithms for Non-smooth Non-convex Optimization
Scaling the Poisson GLM to massive neural datasets through polynomial approximations
IPO: Interpretable Prompt Optimization for Vision-Language Models
Attention in Convolutional LSTM for Gesture Recognition
Private Multiparty Perception for Navigation
A Large-Scale Neural Network Which Recognizes Handwritten Kanji Characters
Distributional Reward Estimation for Effective Multi-agent Deep Reinforcement Learning
Network change point localisation under local differential privacy
Anonymized Histograms in Intermediate Privacy Models
Dynamical Constraints on Computing with Spike Timing in the Cortex
Can LLM Already Serve as A Database Interface? A BIg Bench for Large-Scale Database Grounded Text-to-SQLs
Measuring Progress in Dictionary Learning for Language Model Interpretability with Board Game Models
Visual CoT: Advancing Multi-Modal Language Models with a Comprehensive Dataset and Benchmark for Chain-of-Thought Reasoning
Parallel Tempering With a Variational Reference
Consistent Non-Parametric Methods for Maximizing Robustness
Phase Retrieval Under a Generative Prior
Private Graphon Estimation for Sparse Graphs
On Parallel versus Serial Processing: A Computational Study of Visual Search
Query Complexity of Clustering with Side Information
From Finite to Countable-Armed Bandits
Exocentric-to-Egocentric Video Generation
Gradient Descent Meets Shift-and-Invert Preconditioning for Eigenvector Computation
Learning in Games with Lossy Feedback
Convergence of Adam Under Relaxed Assumptions
Hierarchical Learning Control - An Approach with Neuron-Like Associative Memories
Recurrent Instance Segmentation using Sequences of Referring Expressions
EDML for Learning Parameters in Directed and Undirected Graphical Models
NeoRL: Efficient Exploration for Nonepisodic RL
Temporal Coherence, Natural Image Sequences, and the Visual Cortex
LoTLIP: Improving Language-Image Pre-training for Long Text Understanding
Provable Guarantees for Self-Supervised Deep Learning with Spectral Contrastive Loss
Nonparametric Bayesian Policy Priors for Reinforcement Learning
Teaching Artificial Neural Systems to Drive: Manual Training Techniques for Autonomous Systems
Reconstructing the Image Stitching Pipeline: Integrating Fusion and Rectangling into a Unified Inpainting Model
MG-ViT: A Multi-Granularity Method for Compact and Efficient Vision Transformers
Learning Lie Groups for Invariant Visual Perception
Improving Local Identifiability in Probabilistic Box Embeddings
Differentially Private Anonymized Histograms
Stimulus Encoding by Multidimensional Receptive Fields in Single Cells and Cell Populations in V1 of Awake Monkey
A No-go Theorem for Robust Acceleration in the Hyperbolic Plane
Globally Optimal On-line Learning Rules
Perception of the Structure of the Physical World Using Unknown Multimodal Sensors and Effectors
Consistency of Spectral Partitioning of Uniform Hypergraphs under Planted Partition Model
Diffusion-Inspired Truncated Sampler for Text-Video Retrieval
DreamWaltz: Make a Scene with Complex 3D Animatable Avatars
Address Block Location with a Neural Net System
On Sampling from the Gibbs Distribution with Random Maximum A-Posteriori Perturbations
Finding Bipartite Components in Hypergraphs
Faithful Embeddings for Knowledge Base Queries
Multi-Layered Gradient Boosting Decision Trees
A Generative Model for Parts-based Object Segmentation
Label Disentanglement in Partition-based Extreme Multilabel Classification
Can Graph Neural Networks Count Substructures?
Preventing Gradient Explosions in Gated Recurrent Units
ML4H Auditing: From Paper to Practice
Latent Graphical Model Selection: Efficient Methods for Locally Tree-like Graphs
Sparse Logistic Regression Learns All Discrete Pairwise Graphical Models
Revisiting Sparse Convolutional Model for Visual Recognition
Self-supervised Object-Centric Learning for Videos
Reshaping Visual Datasets for Domain Adaptation
Assessor360: Multi-sequence Network for Blind Omnidirectional Image Quality Assessment
Exponentially Weighted Imitation Learning for Batched Historical Data
Privacy Preserving Human Fall Detection using Video Data
Separable Physics-Informed Neural Networks
Hamiltonian Dynamics with Non-Newtonian Momentum for Rapid Sampling
Orthogonal NMF through Subspace Exploration
Active Information Retrieval
The Thermodynamic Variational Objective
Modality Neutral Techniques for Brain Image Understanding
On the Limitations of Stochastic Pre-processing Defenses
Estimating Heterogeneous Treatment Effects by Combining Weak Instruments and Observational Data
Analyzing Sharpness along GD Trajectory: Progressive Sharpening and Edge of Stability
A Model of Feedback to the Lateral Geniculate Nucleus
Universal Gradient Descent Ascent Method for Nonconvex-Nonconcave Minimax Optimization
Public Wisdom Matters! Discourse-Aware Hyperbolic Fourier Co-Attention for Social Text Classification
Ancestor Sampling for Particle Gibbs
Roadblocks for Temporarily Disabling Shortcuts and Learning New Knowledge
Fast Structured Decoding for Sequence Models
Graph Geometry Interaction Learning
The trade-offs of model size in large recommendation models : 100GB to 10MB Criteo-tb DLRM model
Lookup Table meets Local Laplacian Filter: Pyramid Reconstruction Network for Tone Mapping
Counterfactual Contrastive Learning for Weakly-Supervised Vision-Language Grounding
MSA Generation with Seqs2Seqs Pretraining: Advancing Protein Structure Predictions
Learning direction in global motion: two classes of psychophysically-motivated models
On the Infeasibility of Training Neural Networks with Small Squared Errors
Graph Convolutional Policy Network for Goal-Directed Molecular Graph Generation
Second-order forward-mode optimization of recurrent neural networks for neuroscience
First-Order Algorithms for Min-Max Optimization in Geodesic Metric Spaces
Certified Minimax Unlearning with Generalization Rates and Deletion Capacity
Smoke and Mirrors in Causal Downstream Tasks
Cooperative Heterogeneous Deep Reinforcement Learning
On the relations of LFPs & Neural Spike Trains
Exact Generalization Guarantees for (Regularized) Wasserstein Distributionally Robust Models
What a MESS: Multi-Domain Evaluation of Zero-Shot Semantic Segmentation
Ensemble Learning for Multi-Layer Networks
Improving Adversarial Transferability via Intermediate-level Perturbation Decay
GMSF: Global Matching Scene Flow
Random Sharpness-Aware Minimization
Unsupervised Learning of 3D Structure from Images
Outlier-Robust Wasserstein DRO
UV-free Texture Generation with Denoising and Geodesic Heat Diffusion
UCSG-NET- Unsupervised Discovering of Constructive Solid Geometry Tree
Experience-Guided Search: A Theory of Attentional Control
Learning in Markov Random Fields using Tempered Transitions
How to Initialize your Network? Robust Initialization for WeightNorm & ResNets
A Measure-Theoretic Approach to Kernel Conditional Mean Embeddings
Sourcerer: Sample-based Maximum Entropy Source Distribution Estimation
Ensemble weighted kernel estimators for multivariate entropy estimation
Should I Stop or Should I Go: Early Stopping with Heterogeneous Populations
ATD: Augmenting CP Tensor Decomposition by Self Supervision
Unsupervised Color Constancy
Associative Embedding: End-to-End Learning for Joint Detection and Grouping
Rethinking Knowledge Graph Evaluation Under the Open-World Assumption
In Pursuit of Causal Label Correlations for Multi-label Image Recognition
Temporally changing synaptic plasticity
An Inverse Power Method for Nonlinear Eigenproblems with Applications in 1-Spectral Clustering and Sparse PCA
Addressing Resource Scarcity across Sign Languages with Multilingual Pretraining and Unified-Vocabulary Datasets
Neural Networks for Model Matching and Perceptual Organization
Off-Policy Imitation Learning from Observations
CAPro: Webly Supervised Learning with Cross-modality Aligned Prototypes
Sparse Signal Recovery Using Markov Random Fields
IA-RED$^2$: Interpretability-Aware Redundancy Reduction for Vision Transformers
PLASTIC: Improving Input and Label Plasticity for Sample Efficient Reinforcement Learning
Temporal Abstraction in Temporal-difference Networks
Learning diffusion at lightspeed
Improving Variational Autoencoders with Inverse Autoregressive Flow
Learning Dynamics of Attention: Human Prior for Interpretable Machine Reasoning
On the Optimal Time Complexities in Decentralized Stochastic Asynchronous Optimization
Partial Transportability for Domain Generalization
Limitations of the empirical Fisher approximation for natural gradient descent
Towards a Unified Analysis of Kernel-based Methods Under Covariate Shift
Factorizable Graph Convolutional Networks
Align then Fusion: Generalized Large-scale Multi-view Clustering with Anchor Matching Correspondences
When Is Generalizable Reinforcement Learning Tractable?
HiFi-GAN: Generative Adversarial Networks for Efficient and High Fidelity Speech Synthesis
Probabilistic Differential Dynamic Programming
Processing of missing data by neural networks
Greatness in Simplicity: Unified Self-Cycle Consistency for Parser-Free Virtual Try-On
The 'tree-dependent components' of natural scenes are edge filters
A state-space model of cross-region dynamic connectivity in MEG/EEG
Wasserstein Quantum Monte Carlo: A Novel Approach for Solving the Quantum Many-Body Schrödinger Equation
A self consistent theory of Gaussian Processes captures feature learning effects in finite CNNs
Faster Projection-free Convex Optimization over the Spectrahedron
Faster Matchings via Learned Duals
Learning Domain-Aware Detection Head with Prompt Tuning
Breaking Audio CAPTCHAs
Wavelet Feature Maps Compression for Image-to-Image CNNs
Mining Unseen Classes via Regional Objectness: A Simple Baseline for Incremental Segmentation
Shape analysis for time series
A Three Tiered Approach for Articulated Object Action Modeling and Recognition
Contextual Games: Multi-Agent Learning with Side Information
APRICODD: Approximate Policy Construction Using Decision Diagrams