Zobrazeno 1 - 10
of 8 066
pro vyhledávání: '"An, Junnan"'
Autor:
Fatoni, Muhammad Hilman, Herneth, Christopher, Li, Junnan, Budiman, Fajar, Ganguly, Amartya, Haddadin, Sami
Markerless motion capture devices such as the Leap Motion Controller (LMC) have been extensively used for tracking hand, wrist, and forearm positions as an alternative to Marker-based Motion Capture (MMC). However, previous studies have highlighted t
Externí odkaz:
http://arxiv.org/abs/2408.17287
Autor:
Li, Junnan, Chen, Lingyun, Ringwald, Johannes, Fortunic, Edmundo Pozo, Ganguly, Amartya, Haddadin, Sami
This study addresses the absence of an identification framework to quantify a comprehensive dynamic model of human and anthropomorphic tendon-driven fingers, which is necessary to investigate the physiological properties of human fingers and improve
Externí odkaz:
http://arxiv.org/abs/2408.13044
This study addresses the critical need for diverse and comprehensive data focused on human arm joint torques while performing activities of daily living (ADL). Previous studies have often overlooked the influence of objects on joint torques during AD
Externí odkaz:
http://arxiv.org/abs/2408.07434
Due to their importance in various emerging applications, efficient algorithms for solving minimax problems have recently received increasing attention. However, many existing algorithms require prior knowledge of the problem parameters in order to a
Externí odkaz:
http://arxiv.org/abs/2407.21372
Large multimodal models (LMMs) are processing increasingly longer and richer inputs. Albeit the progress, few public benchmark is available to measure such development. To mitigate this gap, we introduce LongVideoBench, a question-answering benchmark
Externí odkaz:
http://arxiv.org/abs/2407.15754
Graph anomaly detection (GAD) has been widely applied in many areas, e.g., fraud detection in finance and robot accounts in social networks. Existing methods are dedicated to identifying the outlier nodes that deviate from normal ones. While they hea
Externí odkaz:
http://arxiv.org/abs/2407.05934
In this paper, we study second-order algorithms for the convex-concave minimax problem, which has attracted much attention in many fields such as machine learning in recent years. We propose a Lipschitz-free cubic regularization (LF-CR) algorithm for
Externí odkaz:
http://arxiv.org/abs/2407.03571
We study firms' strategic interactions when each firm may own multiple production technologies, each with its own marginal cost and capacity. Increasing industry concentration by reallocating non-efficient capacity to the largest and most efficient f
Externí odkaz:
http://arxiv.org/abs/2407.03504
Autor:
Hong, Zijin, Yuan, Zheng, Zhang, Qinggang, Chen, Hao, Dong, Junnan, Huang, Feiran, Huang, Xiao
Generating accurate SQL from natural language questions (text-to-SQL) is a long-standing challenge due to the complexities in user question understanding, database schema comprehension, and SQL generation. Conventional text-to-SQL systems, comprising
Externí odkaz:
http://arxiv.org/abs/2406.08426
Inductive knowledge graph completion (KGC) aims to infer the missing relation for a set of newly-coming entities that never appeared in the training set. Such a setting is more in line with reality, as real-world KGs are constantly evolving and intro
Externí odkaz:
http://arxiv.org/abs/2406.01140