▁under ▁the ▁super vision ▁of ▁James ▁Lee . ▁She ▁purs ued ▁her ▁research ▁and ▁generalized ▁the ▁above ▁result , ▁de quant izing ▁other ▁quantum ▁machine ▁learning ▁H HL - based ▁problems : ▁principal ▁component ▁analysis ▁and ▁low - rank ▁st ochastic ▁regression . ▁ ▁Media ▁coverage ▁▁ ▁There ▁was ▁wide ▁media ▁coverage ▁in ▁response ▁to ▁Tang ' s ▁work ▁on ▁using ▁classical ▁computing ▁rather ▁than ▁quantum ▁computing ▁to ▁tack le ▁the ▁recommendation ▁problem , ▁due ▁to ▁the ▁per ception ▁that ▁it ▁elimin ates ▁one ▁of ▁the ▁best ▁examples ▁of ▁quantum ▁speed up . ▁ ▁Some ▁research ers ▁came ▁to ▁the ▁defence ▁of ▁quantum ▁computing ▁such ▁as ▁Robert ▁Young ▁( Direct or ▁of ▁the ▁University ▁of ▁Lanc aster ' s ▁Quant um ▁Technology ▁Centre ), ▁who ▁said ▁in ▁a ▁BBC ▁news ▁article , ▁" If ▁we ▁hadn ' t ▁inv ested ▁in ▁quantum ▁computing , ▁the ▁quantum ▁algorithm ▁that ▁inspired ▁[ Miss ] ▁Tang ▁wouldn ' t ▁have ▁existed ". ▁ ▁Tang ▁herself ▁notes ▁the ▁divis ive ▁nature ▁of ▁comparing ▁classical ▁to ▁quantum ▁algorithms , ▁and ▁the ▁tre pid ation ▁of ▁prov ing ▁her ▁algorithm ▁to ▁her ▁advis er , ▁" I ▁started ▁bel ieving ▁there ▁is ▁a ▁fast ▁classical ▁algorithm , ▁but ▁I ▁couldn ’ t ▁really ▁prove ▁it ▁to ▁myself ▁because ▁Scott ▁[ A ar ons on ] ▁seemed ▁to ▁think ▁there ▁wasn ’ t ▁one , ▁and ▁he ▁was ▁the ▁authority ". ▁ ▁At ▁the ▁age ▁of ▁ 1 8 , ▁Tang ▁was ▁named ▁as ▁one ▁of ▁For bes ▁ 3