Papers
Provably Efficient Offline Reinforcement Learning in Regular Decision Processes
Roberto Cipollone, Anders Jonsson, Alessandro Ronca et al.
Provably Fast Convergence of Independent Natural Policy Gradient for Markov Potential Games
Youbang Sun, Tao Liu, Ruida Zhou et al.
Provably Fast Finite Particle Variants of SVGD via Virtual Particle Stochastic Approximation
Aniket Das, Dheeraj Nagaraj
Provably (More) Sample-Efficient Offline RL with Options
Xiaoyan Hu, Ho-fung Leung
Provably Robust Temporal Difference Learning for Heavy-Tailed Rewards
Semih Cayci, Atilla Eryilmaz
Provably Safe Reinforcement Learning with Step-wise Violation Constraints
Nuoya Xiong, Yihan Du, Longbo Huang
Proximity-Informed Calibration for Deep Neural Networks
Miao Xiong, Ailin Deng, Pang Wei W Koh et al.
Pruning vs Quantization: Which is Better?
Andrey Kuzmin, Markus Nagel, Mart van Baalen et al.
Pseudo-Likelihood Inference
Theo Gruner, Boris Belousov, Fabio Muratore et al.
PTADisc: A Cross-Course Dataset Supporting Personalized Learning in Cold-Start Scenarios
Liya Hu, Zhiang Dong, Jingyuan Chen et al.
PTQD: Accurate Post-Training Quantization for Diffusion Models
Yefei He, Luping Liu, Jing Liu et al.
Public Opinion Field Effect Fusion in Representation Learning for Trending Topics Diffusion
Junliang Li, Yang Yajun, Qinghua Hu et al.
PUCA: Patch-Unshuffle and Channel Attention for Enhanced Self-Supervised Image Denoising
Hyemi Jang, Junsung Park, Dahuin Jung et al.
PUe: Biased Positive-Unlabeled Learning Enhancement by Causal Inference
Xutao Wang, Hanting Chen, Tianyu Guo et al.
PUG: Photorealistic and Semantically Controllable Synthetic Data for Representation Learning
Florian Bordes, Shashank Shekhar, Mark Ibrahim et al.
Punctuation-level Attack: Single-shot and Single Punctuation Can Fool Text Models
wenqiang wang, Chongyang Du, Tao Wang et al.
Puzzlefusion: Unleashing the Power of Diffusion Models for Spatial Puzzle Solving
Sepidehsadat (Sepid) Hossieni, Mohammad Amin Shabani, Saghar Irandoust et al.
PyNeRF: Pyramidal Neural Radiance Fields
Haithem Turki, Michael Zollhöfer, Christian Richardt et al.
QATCH: Benchmarking SQL-centric tasks with Table Representation Learning Models on Your Data
Simone Papicchio, Paolo Papotti, Luca Cagliero
Q-DM: An Efficient Low-bit Quantized Diffusion Model
Yanjing Li, Sheng Xu, Xianbin Cao et al.
QH9: A Quantum Hamiltonian Prediction Benchmark for QM9 Molecules
Haiyang Yu, Meng Liu, Youzhi Luo et al.
QLoRA: Efficient Finetuning of Quantized LLMs
Tim Dettmers, Artidoro Pagnoni, Ari Holtzman et al.
QuACK: Accelerating Gradient-Based Quantum Optimization with Koopman Operator Learning
Di Luo, Jiayu Shen, Rumen Dangovski et al.
QuadAttac$K$: A Quadratic Programming Approach to Learning Ordered Top-$K$ Adversarial Attacks
Thomas Paniagua, Ryan Grainger, Tianfu Wu